Accuracy of an articulated head-and-neck motion model using deep learning-based instance segmentation of skeletal bones in CT scans for image registration in radiotherapy
Walter, A.; Bauer, C. J.; Yawson, A. K.; Hoegen-Saßmannshausen, P.; Adeberg, S.; Debus, J.; Jäkel, O.; Frank, M.; Giske, K.
2025. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 13 (1), 2455752. doi:10.1080/21681163.2025.2455752

AutoPQ: Automating quantile estimation from point forecasts in the context of sustainability
Meisenbacher, S.; Phipps, K.; Taubert, O.; Weiel, M.; Götz, M.; Mikut, R.; Hagenmeyer, V.
2025. Applied Energy, 392, 125931. doi:10.1016/j.apenergy.2025.125931

Structure-preserving neural networks for the regularized entropy-based closure of a linear, kinetic, radiative transport equation
Schotthöfer, S.; Laiu, M. P.; Frank, M.; Hauck, C. D.
2025. Journal of Computational Physics, 533, 113967. doi:10.1016/j.jcp.2025.113967

Search for rare decays of the Z and Higgs bosons to a J / ψ or ψ(2S) meson and a photon in proton-proton collisions at = 13 TeV
Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; u. a.
2025. Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics, 865, 139462. doi:10.1016/j.physletb.2025.139462

Light propagation in free-form dielectric waveguides: a modal perspective. Dissertation
Paszkiewicz-Idzik, M. B.
2025, Mai 16. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000181775

Angular analysis of the B0 → K⁎(892)0μ+μ− decay in proton-proton collisions at s = 13 TeV
Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Benato, L.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; u. a.
2025. Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics, 864, 139406. doi:10.1016/j.physletb.2025.139406

Machine Learning for Intelligent Monitoring of Perovskite Thin-Film Fabrication for Photovoltaics. Dissertation
Laufer, F.
2025, April 29. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000181301

Density regression via Dirichlet process mixtures of normal structured additive regression models
Rodríguez-Álvarez, M. X.; Inácio, V.; Klein, N.
2025. Statistics and Computing, 35 (2), 47. doi:10.1007/s11222-025-10567-0

Anisotropic multidimensional smoothing using Bayesian tensor product P-splines
Bach, P.; Klein, N.
2025. Statistics and Computing, 35 (2), Art.-Nr.: 43. doi:10.1007/s11222-025-10569-y

Organising AI for safety: Identifying structural vulnerabilities to guide the design of AI-enhanced socio-technical systems
Gazos, A.; Kahn, J.; Kusche, I.; Büscher, C.; Götz, M.
2025. Safety Science, 184, 106731. doi:10.1016/j.ssci.2024.106731

Asymptotic-Preserving and Energy Stable Dynamical Low-Rank Approximation for Thermal Radiative Transfer Equations
Frank, M.; Kusch, J.; Patwardhan, C.
2025. Multiscale Modeling & Simulation, 23 (1), 278–312. doi:10.1137/24M1646303

Scalable Method for Bayesian Experimental Design without Integrating over Posterior Distribution
Hoang, V.; Espath, L.; Krumscheid, S.; Tempone, R.
2025. SIAM/ASA Journal on Uncertainty Quantification, 13 (1), 114–139. doi:10.1137/23M1603364

PID-Component – A Web Component for Visualizing (not Only) FAIR Digital Objects
Inckmann, M.; Pfeil, A.; Jejkal, T.
2025. Open Conference Proceedings, 5. doi:10.52825/ocp.v5i.1411

T-matrix representation of optical scattering response: Suggestion for a data format
Asadova, N.; Achouri, K.; Arjas, K.; Auguié, B.; Aydin, R.; Baron, A.; Beutel, D.; Bodermann, B.; Boussaoud, K.; Burger, S.; Choi, M.; Czajkowski, K. M.; Evlyukhin, A. B.; Fazel-Najafabadi, A.; Fernandez-Corbaton, I.; u. a.
2025. Journal of Quantitative Spectroscopy and Radiative Transfer, 333, 109310. doi:10.1016/j.jqsrt.2024.109310

Management of Reference Data in Materials Science and Engineering Exemplified for Creep Data of a Single-Crystalline Ni-Based Superalloy
Ávila C, L. A.; Shakeel, Y.; Gedsun, A.; Forti, M.; Hunke, S.; Han, Y.; Hammerschmidt, T.; Aversa, R.; Olbricht, J.; Chmielowski, M.; Stotzka, R.; Bitzek, E.; Hickel, T.; Skrotzki, B.
2025. Acta Materialia, 286, 120735. doi:10.1016/j.actamat.2025.120735

Improving Efficiency of Parallel Across the Method Spectral Deferred Corrections
Čaklović, G.; Lunet, T.; Götschel, S.; Ruprecht, D.
2025. SIAM Journal on Scientific Computing, 47 (1), A430 – A453. doi:10.1137/24M1649800

Towards a Dataset for Paleographic Details in Historical Torah Scrolls
Frank, L.; Götzelmann, G.; Tonne, D.
2025. Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP, 926–933, SciTePress. doi:10.5220/0013173800003912

TotalSegmentator MRI: Robust Sequence-independent Segmentation of Multiple Anatomic Structures in MRI
Akinci D’Antonoli, T.; Berger, L. K.; Indrakanti, A. K.; Vishwanathan, N.; Weiss, J.; Jung, M.; Berkarda, Z.; Rau, A.; Reisert, M.; Küstner, T.; Walter, A.; Merkle, E. M.; Boll, D. T.; Breit, H.-C.; Nicoli, A. P.; u. a.
2025. Radiology, 314 (2). doi:10.1148/radiol.241613

Unveiling novel structural complexity of spiral carbon nanomaterials: Review on mechanical, thermal, and interfacial behaviors via molecular dynamics
Sharifian, A.; Fareghi, P.; Baghani, M.; Odegard, G. M.; van Duin, A. C. T.; Rajabpour, A.; Wu, J.; Baniassadi, M.
2025. Journal of Molecular Structure, 1321 (Part 1), Art.-Nr.: 139837. doi:10.1016/j.molstruc.2024.139837

Multifacets of lossy compression for scientific data in the Joint-Laboratory of Extreme Scale Computing
Cappello, F.; Acosta, M.; Agullo, E.; Anzt, H.; Calhoun, J.; Di, S.; Giraud, L.; Grützmacher, T.; Jin, S.; Sano, K.; Sato, K.; Singh, A.; Tao, D.; Tian, J.; Ueno, T.; u. a.
2025. Future Generation Computer Systems, 163, Art.-Nr.: 107323. doi:10.1016/j.future.2024.05.022

Democratizing uncertainty quantification
Seelinger, L.; Reinarz, A.; Lykkegaard, M. B.; Akers, R.; Alghamdi, A. M. A.; Aristoff, D.; Bangerth, W.; Bénézech, J.; Diez, M.; Frey, K.; Jakeman, J. D.; Jørgensen, J. S.; Kim, K.-T.; Kent, B. M.; Martinelli, M.; u. a.
2025. Journal of Computational Physics, 521 (Part 1), Art.-Nr.: 113542. doi:10.1016/j.jcp.2024.113542

A Gold Standard Benchmark Dataset for Digital Humanities
Kraus, F.; Blumenröhr, N.; Götzelmann, G.; Tonne, D.; Streit, A.
2025. OM-2024: The 19th International Workshop on Ontology Matching collocated with the 23rd International Semantic Web Conference (ISWC 2024), November 11th, Baltimore, USA, 1–17, RWTH Aachen

Energy efficiency trends in HPC: what high-energy and astrophysicists need to know
Suarez, E.; Amaya, J.; Frank, M.; Freyermuth, O.; Girone, M.; Kostrzewa, B.; Pfalzner, S.
2025. Frontiers in Physics, 13, 1542474. doi:10.3389/fphy.2025.1542474

Enabling Secure Shell Access with OpenID Connect
Gudu, D.; Hardt, M.; Brocke, L.; Zachmann, G.
2025. Computing and Software for Big Science, 9 (1), Article no: 5. doi:10.1007/s41781-025-00136-5

Dynamics of Insight, Emotion Regulation, and Emotional Clarity in Obsessive–Compulsive Disorder
Bischof, C.; Hohensee, N.; Dietel, F. A.; Doebler, P.; Klein, N.; Buhlmann, U.
2025. Cognitive Therapy and Research. doi:10.1007/s10608-025-10595-0

Posterior Concentration Rates for Bayesian Penalized Splines
Bach, P.; Klein, N.
2025. Bayesian Analysis, -1 (-1). doi:10.1214/25-BA1523

Ordinal METAR Cloud Cover Classification in Sentinel-2 Satellite Data
Götz, M.; Wessel, E.; Çayoğlu, U.; Jahani, B.; Debus, C.; Cermak, J.; Streit, A.
2025. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 18, 10674–10683. doi:10.1109/JSTARS.2025.3557931

AUDITOR – Accounting data handling toolbox for opportunistic resources
Boehler, M.; Cube, R. F. von; Fischer, M.; Giffels, M.; Kleinemühl, R.; Kroboth, S.; Rottler, B.; Sammel, D.; Schnepf, M.; Schumacher, M.; Vijayakumar, R.
2025. The European Physical Journal C, 85 (3), 265. doi:10.1140/epjc/s10052-025-13963-y

Boosting distributional copula regression for bivariate binary, discrete and mixed responses
Sanchez, G. B.; Klein, N.; Klinkhammer, H.; Mayr, A.
2025. Statistical Methods in Medical Research, 09622802241313294. doi:10.1177/09622802241313294

Building Blocks for Robust and Effective Semi-Supervised Real-World Object Detection
Kassem Sbeyti, M.; Klein, N.; Nowzad, A.; Sivrikaya, F.; Albayrak, S.
2025. Transactions on Machine Learning Research

Machine learning operations landscape: platforms and tools
Berberi, L.; Kozlov, V.; Nguyen, G.; Sáinz-Pardo Díaz, J.; Calatrava, A.; Moltó, G.; Tran, V.; López García, Á.
2025. Artificial Intelligence Review, 58 (6), 167. doi:10.1007/s10462-025-11164-3

WeedsGalore: A Multispectral and Multitemporal UAV-Based Dataset for Crop and Weed Segmentation in Agricultural Maize Fields
Celikkan, E.; Kunzmann, T.; Yeskaliyev, Y.; Itzerott, S.; Klein, N.; Herold, M.
2025. 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 4767–4777, Institute of Electrical and Electronics Engineers (IEEE)

Enhancing UAV-Based Multispectral Semantic Segmentation Through Feature Engineering
Vollmer, E.; Benz, M.; Kahn, J.; Klug, L.; Volk, R.; Schultmann, F.; Götz, M.
2025. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 18, 6206–6216. doi:10.1109/JSTARS.2025.3537330

Results of the Ontology Alignment Evaluation Initiative 2024
Pour, M. A. N.; Algergawy, A.; Blomqvist, E.; Buche, P.; Chen, J.; Cotovio, P. G.; Coulet, A.; Cufi, J.; Dong, H.; Faria, D.; Ferraz, L.; Hertling, S.; He, Y.; Horrocks, I.; Ibanescu, L.; u. a.
2025. Proceedings of the 19th International Workshop on Ontology Matching (OM 2024), Baltimore, USA, November 11, 2024. Ed.: E. Jiménez-Ruiz, O. Hassanzadeh, C. Trojahn, S. Hertling, H. Li, P. Shvaiko, J. Euzenat, 64 – 97, CEUR-WS

From counting stations to city-wide estimates: data-driven bicycle volume extrapolation
Kaiser, S. K.; Klein, N.; Kaack, L. H.
2025. Environmental Data Science, 4, Art.-Nr.: e13. doi:10.1017/eds.2025.5

Modeling the ratio of correlated biomarkers using copula regression
Berger, M.; Klein, N.; Wagner, M.; Schmid, M.
2025. Statistical Methods in Medical Research. doi:10.1177/09622802241313293

Measurement of multidifferential cross sections for dijet production in proton–proton collisions at
CMS Collaboration; Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Valle, A. E. D.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; u. a.
2025. The European Physical Journal C, 85 (1), 72. doi:10.1140/epjc/s10052-024-13606-8

Bayesian Regularized Regression Copula Processes for Multivariate Responses
Klein, N.; Smith, M. S.; Chisholm, R. A.; Nott, D. J.
2025. Journal of Computational and Graphical Statistics, 1–14. doi:10.1080/10618600.2025.2458504

Deep learning for augmented process monitoring of scalable perovskite thin-film fabrication
Laufer, F.; Götz, M.; Paetzold, U. W.
2025. Energy & Environmental Science. doi:10.1039/D4EE03445G

Enhancement of the photon pair generation rate by spontaneous four-wave mixing in bent waveguides
Paszkiewicz, M.; Rockstuhl, C.
2025. Physical Review A, 111 (1), Art.-Nr.: 013507. doi:10.1103/PhysRevA.111.013507

Copula Modeling and Uncertainty Propagation in Field‐Scale Simulation of CO₂ Fault Leakage
Pettersson, P.; Keilegavlen, E.; Sandve, T. H.; Gasda, S. E.; Krumscheid, S.
2025. Water Resources Research, 61 (1), e2024WR038073. doi:10.1029/2024WR038073

Associations between Emotion Regulation, Symptom Severity, and Affect in Obsessive-Compulsive Disorder
Hohensee, N.; Bischof, C.; Dietel, F. A.; Klein, N.; Doebler, P.; Buhlmann, U.
2025. Journal of Obsessive-Compulsive and Related Disorders, 44, Article no: 100934. doi:10.1016/j.jocrd.2024.100934

Capturing the Variability of the Nocturnal Boundary Layer through Localized Perturbation Modeling
Kaiser, A.; Vercauteren, N.; Krumscheid, S.
2025. Journal of the Atmospheric Sciences, 82 (1), 119–138. doi:10.1175/JAS-D-24-0036.1

Solving stationary nonlinear Fokker-Planck equations via sampling
Li, L.; Tang, Y.; Zhang, J.
2025. SIAM journal on applied mathematics, 85 (1), 249–277. doi:10.1137/23M1616054

Numerical solution of a parameter estimation problem arising in Prompt-Gamma Neutron Activation Analysis
Jesser, A.; Krycki, K.; Frank, M.
2024. Applied Mathematics in Science and Engineering, 32 (1), Article no: 2336170. doi:10.1080/27690911.2024.2336170

Optimization of AI Methods on Distributed-Memory Computing Architectures. Dissertation
Coquelin, D.
2024, Dezember 17. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000176552

FAIR Digital Objects for the Realization of Globally Aligned Data Spaces
Blumenröhr, N.; Ost, P.-J.; Kraus, F.; Streit, A.
2024. 2024 IEEE International Conference on Big Data (BigData), 15th -18th December 2024, Washington DC, USA., 374–383, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData62323.2024.10825796

Quantifying agricultural land-use intensity for spatial biodiversity modelling: implications of different metrics and spatial aggregation methods
Roilo, S.; Paulus, A.; Alarcón-Segura, V.; Kock, L.; Beckmann, M.; Klein, N.; Cord, A. F.
2024. Landscape Ecology, 39 (3), Art.-Nr.: 55. doi:10.1007/s10980-024-01853-9

Personalized federated learning for improving radar based precipitation nowcasting on heterogeneous areas
Sáinz-Pardo Díaz, J.; Castrillo, M.; Bartok, J.; Cachá, I. H.; Ondík, I. M.; Martynovskyi, I.; Alibabaei, K.; Berberi, L.; Kozlov, V.; López García, Á.
2024. Earth Science Informatics, 17 (6), 5561–5584. doi:10.1007/s12145-024-01438-9

Generating synthetic energy time series: A review
Turowski, M.; Heidrich, B.; Weingärtner, L.; Springer, L.; Phipps, K.; Schäfer, B.; Mikut, R.; Hagenmeyer, V.
2024. Renewable and Sustainable Energy Reviews, 206, 114842. doi:10.1016/j.rser.2024.114842

FRSZ2 for In-Register Block Compression Inside GMRES on GPUs
Grützmacher, T.; Underwood, R.; Di, S.; Cappello, F.; Anzt, H.
2024. Proceedings of SC24-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, 240 – 249, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SCW63240.2024.00038

A stochastic Galerkin lattice Boltzmann method for incompressible fluid flows with uncertainties
Zhong, M.; Xiao, T.; Krause, M. J.; Frank, M.; Simonis, S.
2024. Journal of Computational Physics, 517, 113344. doi:10.1016/j.jcp.2024.113344

Up and down quark structure of the proton
D0 Collaboration; Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Avila, C.; Badaud, F.; u. a.
2024. Physical Review D, 110 (9), L091101. doi:10.1103/PhysRevD.110.L091101

A conditional deep learning model for super-resolution reconstruction of small-scale turbulent structures in particle-Laden flows
Tofighian, H.; Denev, J. A.; Kornev, N.
2024. Physics of Fluids, 36 (11), Art.-Nr.: 115173. doi:10.1063/5.0235192

Measurement of the polarizations of prompt and non-prompt J/ψ and ψ (2S) mesons produced in pp collisions at = 13 TeV
Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; u. a.
2024. Physics Letters B, 858, Art.-Nr.: 139044. doi:10.1016/j.physletb.2024.139044

Carrier-phase direct numerical simulation and flamelet modeling of NO formation in a pulverized coal/ammonia co-firing flame
Wen, X.; Shamooni, A.; Zirwes, T.; Stein, O. T.; Kronenburg, A.; Hasse, C.
2024. Combustion and Flame, 269, 113722. doi:10.1016/j.combustflame.2024.113722

Evolution of SSH with OpenId Connect
Hardt, M.; Gudu, D.; Zachmann, G.; Brocke, L.
2024. Proceedings of International Symposium on Grids & Clouds (ISGC) 2024, Taiwan, 24th - 29th March 2024, Art.-Nr.: 23, Scuola Internazionale Superiore di Studi Avanzati (SISSA). doi:10.22323/1.458.0023

Towards Unifying Anatomy Segmentation: Automated Generation of a Full-Body CT Dataset
Jaus, A.; Seibold, C.; Hermann, K.; Shahamiri, N.; Walter, A.; Giske, K.; Haubold, J.; Kleesiek, J.; Stiefelhagen, R.
2024. 2024 IEEE International Conference on Image Processing (ICIP), Abu Dhabi, 27th-30th October 2024, 41–47, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICIP51287.2024.10647307

Informed Spectral Normalized Gaussian Processes for Trajectory Prediction
Schlauch, C.; Wirth, C.; Klein, N.
2024. ECAI 2024 – 27th European Conference on Artificial Intelligence, 19–24 October 2024, Santiago de Compostela, Spain – Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024). Ed.: U. Endriss, 3023 – 3030, IOS Press. doi:10.3233/FAIA240843

Harnessing Orthogonality to Train Low-Rank Neural Networks
Coquelin, D.; Flügel, K.; Weiel, M.; Kiefer, N.; Debus, C.; Streit, A.; Götz, M.
2024. ECAI 2024 : 27th European Conference on Artificial Intelligence 19–24 October 2024, Santiago de Compostela, Spain Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024 ; Proceedings. Ed.: U. Endriss, 2106–2113, IOS Press. doi:10.3233/FAIA240729

Taylor Expansion in Neural Networks: How Higher Orders Yield Better Predictions
Zwerschke, P.; Weyrauch, A.; Götz, M.; Debus, C.
2024. ECAI 2024 – 27th European Conference on Artificial Intelligence, 19–24 October 2024, Santiago de Compostela, Spain – Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024). Ed.: U. Endriss, 2983–2989, IOS Press. doi:10.3233/FAIA240838

Enhancement of the photon pair generation rate in bent waveguides
Paszkiewicz, M.; Sipe, J. E.; Rockstuhl, C.
2024. M. A. Kahan & C. Merrill (Hrsg.), Optical Modeling and Performance Predictions XIV, Art.-Nr.: 131290R, SPIE. doi:10.1117/12.3026907

Flow characteristics at the interface during droplet formation in a flow-focusing microfluidic channel—numerical analysis of dripping and jetting regimes
Grigorov, E.; Denev, J. A.; Kirov, B.; Galabov, V.
2024. Acta Mechanica, 235 (10), 6057–6075. doi:10.1007/s00707-024-04031-9

K and Λ ( two-particle femtoscopic correlations in PbPb collisions at = 5.02 TeV
Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; u. a.
2024. Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics, 857, 138936. doi:10.1016/j.physletb.2024.138936

A Fully Parallelized and Budgeted Multilevel Monte Carlo Method and the Application to Acoustic Waves
Baumgarten, N.; Krumscheid, S.; Wieners, C.
2024. SIAM/ASA Journal on Uncertainty Quantification, 12 (3), 901–931. doi:10.1137/23M1588354

Numerical Simulation of Thermal Decomposition of Polyethylene with a Single-Particle Model
Zhang, F.; Cao, J.; Zirwes, T.; Netsch, N.; Tavakkol, S.; Zhang, R.; Bockhorn, H.; Stapf, D.
2024. Advances in Computational Heat and Mass Transfer – Proceedings of the 14th International Conference on Computational Heat and Mass Transfer (ICCHMT 2023), 4-8 September, 2023, Düsseldorf, Germany, Volume 1. Ed.: A. Benim, 180 – 191, Springer International Publishing. doi:10.1007/978-3-031-67241-5_17

Mechanism of activation and autophosphorylation of a histidine kinase
Kansari, M.; Idiris, F.; Szurmant, H.; Kubař, T.; Schug, A.
2024. Communications Chemistry, 7 (1), Art.-Nr.: 196. doi:10.1038/s42004-024-01272-6

Emotion Regulation in Obsessive-Compulsive Disorder: An Ecological Momentary Assessment Study
Bischof, C.; Hohensee, N.; Dietel, F. A.; Doebler, P.; Klein, N.; Buhlmann, U.
2024. Behavior Therapy, 55 (5), 935–949. doi:10.1016/j.beth.2024.01.011

Assessing the potential of free-tropospheric water vapour isotopologue satellite observations for improving the analyses of convective events
Schneider, M.; Toride, K.; Khosrawi, F.; Hase, F.; Ertl, B.; Diekmann, C. J.; Yoshimura, K.
2024. Atmospheric Measurement Techniques, 17 (17), 5243–5259. doi:10.5194/amt-17-5243-2024

Multi-Objective Optimization for Multi-Agent Injection Strategies in Subsurface CO2 Storage
Pettersson, P.; Krumscheid, S.; Gasda, S.
2024. Conference Proceedings, ECMOR 2024, 1–14, European Association of Geoscientists and Engineers (EAGE). doi:10.3997/2214-4609.202437062

The role of thermodiffusion and dimensionality in the formation of cellular instabilities in hydrogen flames
Zirwes, T.; Zhang, F.; Kaiser, T. L.; Oberleithner, K.; Stein, O. T.; Bockhorn, H.; Kronenburg, A.
2024. Proceedings of the Combustion Institute, 40 (1-4), Art.-Nr.: 105665. doi:10.1016/j.proci.2024.105665

Evidence for tWZ production in proton-proton collisions at = 13 TeV in multilepton final states
Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Liko, D.; Mikulec, I.; Schieck, J.; u. a.
2024. Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics, 855, Art.-Nr.: 138815. doi:10.1016/j.physletb.2024.138815

From method development to software integration: A comprehensive approach to geostatistical variogram uncertainty. Dissertation
Mälicke, M.
2024, Juli 12. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000172259

Divergent Associations of Slow‐Wave Sleep versus Rapid Eye Movement Sleep with Plasma Amyloid‐Beta
Rosenblum, Y.; Pereira, M.; Stange, O.; Weber, F. D.; Bovy, L.; Tzioridou, S.; Lancini, E.; Neville, D. A.; Klein, N.; de Wolff, T.; Stritzke, M.; Kersten, I.; Uhr, M.; Claassen, J. A. H. R.; Steiger, A.; u. a.
2024. Annals of Neurology, 96 (1), 46–60. doi:10.1002/ana.26935

Search for high-mass exclusive diphoton production with tagged protons in proton-proton collisions at √s = 13 TeV
CMS Collaboration; TOTEM Collaboration; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; u. a.
2024. Physical Review D, 110 (1), Art.-Nr.: 012010. doi:10.1103/PhysRevD.110.012010

Scalable multiscale-spectral GFEM with an application to composite aero-structures
Bénézech, J.; Seelinger, L.; Bastian, P.; Butler, R.; Dodwell, T.; Ma, C.; Scheichl, R.
2024. Journal of Computational Physics, 508, Art.-Nr.: 113013. doi:10.1016/j.jcp.2024.113013

ReCycle: Fast and Efficient Long Time Series Forecasting with Residual Cyclic Transformers
Weyrauch, A.; Steens, T.; Taubert, O.; Hanke, B.; Eqbal, A.; Götz, E.; Streit, A.; Götz, M.; Debus, C.
2024. 2024 IEEE Conference on Artificial Intelligence (CAI), Singapore, Singapore, 25-27 June 2024, 1187–1194, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CAI59869.2024.00212

Making Federated Learning Accessible to Scientists: The AI4EOSC Approach
Sáinz-Pardo Díaz, J.; Heredia Canales, A.; Heredia Cachá, I.; Tran, V.; Nguyen, G.; Alibabaei, K.; Obregón Ruiz, M.; Rebolledo Ruiz, S.; López García, Á.
2024. IH&MMSec ’24: Proceedings of the 2024 ACM Workshop on Information Hiding and Multimedia Security, 253 – 264, Association for Computing Machinery (ACM). doi:10.1145/3658664.3659642

Optimizing the trajectories of freeform waveguides using a modal theory
Paszkiewicz, M.; Sukhova, M.; Dörfler, W.; Rockstuhl, C.
2024. D. G. Smith & A. Erdmann (Hrsg.), Computational Optics 2024, Ed.: D. Smith, A. Erdmann, Art.-Nr.: PC1302305, SPIE. doi:10.1117/12.3014421

Ultra-high-granularity detector simulation with intra-event aware generative adversarial network and self-supervised relational reasoning
Hashemi, B.; Hartmann, N.; Sharifzadeh, S.; Kahn, J.; Kuhr, T.
2024. Nature Communications, 15 (1), Art.-Nr.: 4916. doi:10.1038/s41467-024-49104-4

Annotationen im Medienwandel
Ernst, F.; Götzelmann, G.; Hegel, P.; Kalchreuter, C.; Krewet, M.; Rapp, A.; Schenk, T.; Tonne, D.
2024. Logbuch Wissensgeschichte Abschlusspublikation SFB 980 Becker-Sawatzky, Mira / Wächter, Katrin / Wendt, Helge / Dadaş, Şirin / Eusterschulte, Anne / Hasselmann, Kristiane / James Johnston, Andrew / Quenstedt, Falk / Reufer, Claudia / Trauer, Hanna Zoe / Vogel, Christian, 421–438, Harrassowitz Verlag. doi:10.13173/9783447121804

Feasibility of Forecasting Highly Resolved Power Grid Frequency Utilizing Temporal Fusion Transformers
Pütz, S.; El Ashhab, H.; Hertel, M.; Mikut, R.; Götz, M.; Hagenmeyer, V.; Schäfer, B.
2024. e-Energy ’24: Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems, 447–453, Association for Computing Machinery (ACM). doi:10.1145/3632775.3661963

A Probabilistic Model for Asynchronous Iterative Methods
Nayak, P.; Anzt, H.
2024. 2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), San Francisco, CA, USA, 27-31 May 2024, 260–269, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IPDPSW63119.2024.00064

Identifying and Understanding Scientific Network Flows
Hoeft, B.; Attebury, G.; Babik, M.; Carder, D.; Chown, T.; Hanushevky, A.; Lake, A.; Lambert, M.; Letts, J.; McKee, S.; Newell, K.; Sullivan, T.
2024. 26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023), Norfolk, 8th-12th May 2023, Art-nr.:01036, EDP Sciences - Web of Conferences. doi:10.1051/epjconf/202429501036

Overcoming obstacles to IPv6 on WLCG
Hoeft, B.; Babik, M.; Bly, M.; Buraglio, N.; Chown, T.; Christidis, D.; Chudoba, J.; DeMar, P.; Flix Molina, J.; Grigoras, C.; Ito, H.; Kelsey, D.; Martelli, E.; McKee, S.; Misa Moreira, C.; u. a.
2024. 26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023), Norfolk, VA, 8th-12th May 2023, Art-Nr.: 07036, EDP Sciences - Web of Conferences. doi:10.1051/epjconf/202429507036

Longitudinal phase space density tomography constrained by the Vlasov-Fokker-Planck equation
Donoso, F.; Santamaria Garcia, A.; Mueller, A.-S.; Bruendermann, E.; Frank, M.; Reissig, M.; Funkner, S.
2024. 15th International Particle Accelerator Conference, Nashville, Tennessee : May 19-24, 2024, Nashville, Tennessee, USA : proceedings. Ed.: F. Pilat, 2350–2353, JACoW Publishing. doi:10.18429/JACoW-IPAC2024-WEPG55

iMagine, AI-supported imaging data and services for ocean and marine science
Sipos, G.; Schaap, D.; Lopez Garcia, A.; Kozlov, V.
2024. International Conference on Marine Data and Information Systems - Proceedings Volume. International Conference on Marine Data and Information Systems - Proceedings Volume., International Conference on Marine Data and Information Systems (IMDIS 2024 2024), Bergen, Norwegen, 27.05.2024–29.05.2024, 303–305

Search for an exotic decay of the Higgs boson into a Z boson and a pseudoscalar particle in proton-proton collisions at √s = 13 TeV
Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Liko, D.; Mikulec, I.; Schieck, J.; u. a.
2024. Physics Letters B, 852, Art.-Nr.: 138582. doi:10.1016/j.physletb.2024.138582

Distributional Regression for Data Analysis
Klein, N.
2024. Annual Review of Statistics and Its Application, 11, 321–346. doi:10.1146/annurev-statistics-040722-053607

Machine Learning from Evolution. Dissertation
Taubert, O.
2024, April 19. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000170101

A Cascadic Parareal Method for Parallel-in-Time Simulation of Compressible Supersonic Flow
Chen, Y.-C.; Nakajima, K.
2024. Journal of Information Processing, 32, 369 – 379. doi:10.2197/ipsjjip.32.369

Bayesian Conditional Transformation Models
Carlan, M.; Kneib, T.; Klein, N.
2024. Journal of the American Statistical Association, 119 (546), 1360–1373. doi:10.1080/01621459.2023.2191820

Bivariate Analysis of Birth Weight and Gestational Age by Bayesian Distributional Regression with Copulas
Rathjens, J.; Kolbe, A.; Hölzer, J.; Ickstadt, K.; Klein, N.
2024. Statistics in Biosciences, 16 (1), 290–317. doi:10.1007/s12561-023-09396-4

Effects of Intrinsic Instabilities on the Response of Premixed Hydrogen/Air Conical Flames to Inlet Flow Perturbations
Yang, L.; Wang, Y.; Zirwes, T.; Zhang, F.; Bockhorn, H.; Chen, Z.
2024. Flow, Turbulence and Combustion, 112 (4), 1275–1297. doi:10.1007/s10494-024-00535-5

Approximation and Optimization of Compute-Intensive Environmental Simulations through Machine Learning Methods. Dissertation
Azmi, E.
2024, März 5. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000169007

Flexible specification testing in quantile regression models
Kutzker, T.; Klein, N.; Wied, D.
2024. Scandinavian Journal of Statistics, 51 (1), 355–383. doi:10.1111/sjos.12671

Projektkurs für Mädels: Mit Mathe und KI reale Probleme lösen
Hofmann, S.; Schönbrodt, S.
2024. Mitteilungen der Deutschen Mathematiker-Vereinigung, 32 (2), 124–126. doi:10.1515/dmvm-2024-0037

Study of azimuthal anisotropy of ϒ(1S) mesons in pPb collisions at √NN = 8.16 TeV
Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; u. a.
2024. Physics Letters B, 850, Art.-Nr.: 138518. doi:10.1016/j.physletb.2024.138518

OMI-based emission source classification in East China and its spatial redistribution in view of pollution control measures
Zara, M.; van der A, R.; Ding, J.; Stavrakou, T.; Boersma, F.
2024. Environmental Monitoring and Assessment, 196 (3), Art.-Nr.: 323. doi:10.1007/s10661-024-12421-8

Search for new Higgs bosons via same-sign top quark pair production in association with a jet in proton-proton collisions at = 13 TeV
Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; u. a.
2024. Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics, 850, Art.-Nr.: 138478. doi:10.1016/j.physletb.2024.138478

Measurements of azimuthal anisotropy of nonprompt D mesons in PbPb collisions at = 5.02 TeV
Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; u. a.
2024. Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics, 850, Art.-Nr.: 138389. doi:10.1016/j.physletb.2023.138389

Portable Mixed Precision Algebraic Multigrid on High Performance GPUs. Dissertation
Tsai, Y.-H.
2024, Februar 29. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000168914

Assessment of dynamic characteristics of fluidized beds via numerical simulations
Zhang, F.; Tavakkol, S.; Dercho, S.; Zhou, J.; Zirwes, T.; Zeller, M.; Vogt, J.; Zhang, R.; Bockhorn, H.; Stapf, D.
2024. Physics of Fluids, 36 (2), Art.-Nr.: 023348. doi:10.1063/5.0189519

Essential parameters needed for a U-Net-based segmentation of individual bones on planning CT images in the head and neck region using limited datasets for radiotherapy application
Yawson, A. K.; Walter, A.; Wolf, N.; Klüter, S.; Hoegen, P.; Adeberg, S.; Debus, J.; Frank, M.; Jäkel, O.; Giske, K.
2024. Physics in Medicine & Biology, 69 (3), Art.-Nr.: 035008. doi:10.1088/1361-6560/ad1996

Approximation method for fast calculation of transmission in multi-mode waveguides
Paszkiewicz, M.; Sukhova, M.; Dörfler, W.; Rockstuhl, C.
2024. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 41 (2), 174 – 184. doi:10.1364/JOSAA.504950

BannMI deciphers potential n -to-1 information transduction in signaling pathways to unravel message of intrinsic apoptosis
Schmidt, B.; Sers, C.; Klein, N.
2024. (T. Lengauer, Hrsg.) Bioinformatics Advances, 4 (1), Article no: vbad175. doi:10.1093/bioadv/vbad175

Semi-Structured Distributional Regression
Rügamer, D.; Kolb, C.; Klein, N.
2024. The American Statistician, 78 (1), 88–99. doi:10.1080/00031305.2022.2164054

Mathematische Grundlagen des Data Cleanings
Eckert, J.; Schönbrodt, S.
2024. Beiträge zum Mathematikunterricht 2024: 57. Jahrestagung der Gesellschaft für Didaktik der Mathematik .vom 04.03.2024 bis 08.03.2024 in Essen. Hrsg.: P. Ebers, F. Rösken, B. Barzel, A. Büchter, F. Schacht & P. Scherer, Gesellschaft für Didaktik der Mathematik (GDM). doi:10.17877/DE290R-25151

Nutzung künstlicher Intelligenz zur Aufspürung von Geisternetzen in Küstengewässern
Schumacher, M.; Götz, M.; Dederer, G.; Lee, M.
2024. Journal of applied hydrography = Hydrographische Nachrichten, 127 (3), 20–25. doi:10.23784/HN127-04

Search for CP violation in decays in proton–proton collisions at
CMS Collaboration; Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; u. a.
2024. The European Physical Journal C, 84 (12), Art.-Nr.: 1264. doi:10.1140/epjc/s10052-024-13244-0

Architectural insights into and training methodology optimization of Pangu-Weather
To, D.; Quinting, J.; Hoshyaripour, G. A.; Götz, M.; Streit, A.; Debus, C.
2024. Geoscientific Model Development, 17 (23), 8873–8884. doi:10.5194/gmd-17-8873-2024

Quantifying the Impact of Regional-Scale Pressure Interference on Commercial CO2 Storage Targets for Multiple Licenses
Gasda, S.; Sandve, T. H.; Tveit, S.; Landa-Marban, D.; Pettersson, P.; Krumscheid, S.; Mykkeltvedt, T. S.; Dahle, H.
2024. SSRN Electronic Journal. doi:10.2139/ssrn.5053633

Resource-aware research on Universe and Matter: call-to-action in digital transformation
Bruers, B.; Cruces, M.; Demleitner, M.; Duckeck, G.; Düren, M.; Eich, N.; Enßlin, T.; Erdmann, J.; Erdmann, M.; Fackeldey, P.; Felder, C.; Fischer, B.; Fröse, S.; Funk, S.; Gasthuber, M.; u. a.
2024. The European Physical Journal Special Topics. doi:10.1140/epjs/s11734-024-01436-4

Vectorized Highly Parallel Density-based Clustering for Applications with Noise
Xavier, J. A.; Muriedas, J. P. G. H.; Nassyr, S.; Sedona, R.; Götz, M.; Streit, A.; Riedel, M.; Cavallaro, G.
2024. IEEE Access, 12, 181679–181692. doi:10.1109/ACCESS.2024.3507193

The Deep Promotion Time Cure Model
Medina-Olivares, V.; Lessmann, S.; Klein, N.
2024. IEEE Transactions on Neural Networks and Learning Systems, 35 (12), 18848–18858. doi:10.1109/TNNLS.2024.3398559

Truly Multivariate Structured Additive Distributional Regression
Kock, L.; Klein, N.
2024. Journal of Computational and Graphical Statistics, 1–13. doi:10.1080/10618600.2024.2434181

Observation of the decay
CMS Collaboration; Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Valle, A. E. D.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Liko, D.; Mikulec, I.; u. a.
2024. The European Physical Journal C, 84 (10), Art.-Nr.: 1062. doi:10.1140/epjc/s10052-024-13114-9

Sparse Explanations of Neural Networks Using Pruned Layer-Wise Relevance Propagation
Yanez Sarmiento, P.; Witzke, S.; Klein, N.; Renard, B. Y.
2024. Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9–13, 2024, Proceedings, Part IV, 336–351, Springer. doi:10.1007/978-3-031-70359-1_20

Investigating Calibration and Corruption Robustness of Post-hoc Pruned Perception CNNs: An Image Classification Benchmark Study
Mitra, P.; Schwalbe, G.; Klein, N.
2024. Proceedings of the IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), 17th - 21st June 2024, Seattle, 3542–3552

Boosting distributional copula regression for bivariate time-to-event data
Sanchez, G. B.; Klein, N.; Groll, A.; Mayr, A.
2024. Proceedings of the 38th International Workshop on Statistical Modelling, 14th - 19th July, 2024, Durham, UK. Eds.: Jochen Einbeck, Reza Drikvandi, Georgios Karagiannis, Konstantinos Perrakis, Qing Zhang, 75–80

Cost-Sensitive Uncertainty-Based Failure Recognition for Object Detection
Kassem-Sbeyti, M.; Karg, M.; Wirth, C.; Klein, N.; Albayrak, S.
2024. Uncertainty in Artificial Intelligence, 1890–1900

Intergenerational Social Mobility in the United States: A Multivariate Analysis Using Distributional Regression
März, A.; Klein, N.; Kneib, T.; Mußhoff, O.
2024. Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science : Essays in Honour of Wolfgang Schmid. Ed.: S. Knoth, 295–335, Springer Nature Switzerland. doi:10.1007/978-3-031-69111-9_15

Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications
Stasinopoulos, M. D.; Kneib, T.; Klein, N.; Mayr, A.; Heller, G. Z.
2024. Cambridge University Press (CUP). doi:10.1017/9781009410076

Loss Prediction and 3D Trajectory Design of Photonic Wire Bonds using Artificial Neural Networks (ANN)
Bao, Y.; Paszkiewicz, M.; Krimmer, J.; Freude, W.; Randel, S.; Rockstuhl, C.; Koos, C.
2024. Conference on Lasers and Electro-Optics: Science and Innovations 2024 (CLEO), Charlotte, USA, May 5th-10th 2024, Art.-Nr.: SM1I.3, Optica Publishing Group (OSA). doi:10.1364/CLEO_SI.2024.SM1I.3

Reconstructing Particle Decay Trees with Quantum Graph Neural Networks for High Energy Physics
Strobl, M.; Kuehn, E.; Fischer, M.; Streit, A.
2024. 21st International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2022), Bari, I, October 23-28, 2022

Improving Noisy Hybrid Quantum Graph Neural Networks for Particle Decay Tree Reconstruction
Strobl, M.; Kuehn, E.; Fischer, M.; Streit, A.
2024. EPJ Web of Conferences, 295, Article no: 12004. doi:10.1051/epjconf/202429512004

Ginkgo - A math library designed to accelerate Exascale Computing Project science applications
Cojean, T.; Nayak, P.; Ribizel, T.; Beams, N.; Mike Tsai, Y.-H.; Koch, M.; Göbel, F.; Grützmacher, T.; Anzt, H.
2024. The International Journal of High Performance Computing Applications. doi:10.1177/10943420241268323

Model Fusion via Neuron Transplantation
Öz, M.; Kiefer, N.; Debus, C.; Hörter, J.; Streit, A.; Götz, M.
2024. Machine Learning and Knowledge Discovery in Databases. Research Track : European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9–13, 2024, Proceedings, Part IV. Ed. by Albert Bifet, Jesse Davis, Tomas Krilavičius, Meelis Kull, Eirini Ntoutsi, Indrė Žliobaitė, 3–19, Springer Nature Switzerland. doi:10.1007/978-3-031-70359-1_1

Scalable Estimation for Structured Additive Distributional Regression
Umlauf, N.; Seiler, J.; Wetscher, M.; Simon, T.; Lang, S.; Klein, N.
2024. Journal of Computational and Graphical Statistics, 1–17. doi:10.1080/10618600.2024.2388604

Automatic heliostat learning for in situ concentrating solar power plant metrology with differentiable ray tracing
Pargmann, M.; Ebert, J.; Götz, M.; Maldonado Quinto, D.; Pitz-Paal, R.; Kesselheim, S.
2024. Nature Communications, 15 (1), Art.-Nr.: 6997. doi:10.1038/s41467-024-51019-z

Wortvorschläge beim Chatten : KI und natürliche Sprachverarbeitung im Stochastikunterricht
Hofmann, S.; Frank, M.
2024. Mathematik lehren, (244), 24–29

Carrier-phase direct numerical simulation and flamelet modeling of alkali metal emissions from pulverized biomass flames
Shamooni, A.; Wen, X.; Debiagi, P.; Stagni, A.; Gärtner, J. W.; Zirwes, T.; Stein, O. T.; Hasse, C.; Kronenburg, A.
2024. Proceedings of the Combustion Institute, 40 (1-4), 105309. doi:10.1016/j.proci.2024.105309

Modeling and Quantifying Parameter Uncertainty of Co‐Seismic Non‐Classical Nonlinearity in Rocks
Niu, Z.; Gabriel, A.-A.; Seelinger, L.; Igel, H.
2024. Journal of Geophysical Research: Solid Earth, 129 (1). doi:10.1029/2023JB027149

Sequential Estimation Using Hierarchically Stratified Domains with Latin Hypercube Sampling
Krumscheid, S.; Pettersson, P.
2024. Monte Carlo and Quasi-Monte Carlo Methods : MCQMC 2022, Linz, Austria, July 17–22. Ed.: A. Hinrichs, 393–411, Springer International Publishing. doi:10.1007/978-3-031-59762-6_19

Efficient interface to the GridKa tape storage system
Musheghyan, H.; Petzold, A.; Ressmann, D.; Konstantinov, P.; Lobontu, D.-D.; Gottmann, A.; Ambroj Pérez, S.; Mol, X.
2024. (R. De Vita, X. Espinal, P. Laycock & O. Shadura, Hrsg.) EPJ Web of Conferences, 295, Art.-Nr.: 01020. doi:10.1051/epjconf/202429501020

CPU Performance Study for HEP Workloads with Respect to the Number of Single-core Slots
Schnepf, M. J.; Fischer, M.; Petzold, A.
2024. (R. De Vita, X. Espinal, P. Laycock & O. Shadura, Hrsg.) EPJ Web of Conferences, 295, Art.-Nr.: 07010. doi:10.1051/epjconf/202429507010

Structure and dynamics of hexagonal cells in H/CO flames
Zirwes, T.; Eckart, S.; Zhang, F.; Kaiser, T. L.; Oberleithner, K.; Stein, O. T.; Bockhorn, H.; Kronenburg, A.
2024. Proceedings of the Combustion Institute, 40 (1-4), 105332. doi:10.1016/j.proci.2024.105332

Towards a platform-portable linear algebra backend for OpenFOAM
Olenik, G.; Koch, M.; Boutanios, Z.; Anzt, H.
2024. Meccanica. doi:10.1007/s11012-024-01806-1

PETNet–Coincident Particle Event Detection using Spiking Neural Networks
Debus, J.; Debus, C.; Dissertori, G.; Götz, M.
2024. 2024 Neuro Inspired Computational Elements Conference (NICE), 9 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/NICE61972.2024.10549584

Earth Virtualization Engines (EVE)
Stevens, B.; Adami, S.; Ali, T.; Anzt, H.; Aslan, Z.; Attinger, S.; Bäck, J.; Baehr, J.; Bauer, P.; Bernier, N.; Bishop, B.; Bockelmann, H.; Bony, S.; Brasseur, G.; Bresch, D. N.; u. a.
2024. Earth System Science Data, 16 (4), 2113 – 2122. doi:10.5194/essd-16-2113-2024

Segmentation of 71 Anatomical Structures Necessary for the Evaluation of Guideline-Conforming Clinical Target Volumes in Head and Neck Cancers
Walter, A.; Hoegen-Saßmannshausen, P.; Stanic, G.; Rodrigues, J. P.; Adeberg, S.; Jäkel, O.; Frank, M.; Giske, K.
2024. Cancers, 16 (2), Art.-Nr.: 415. doi:10.3390/cancers16020415

Sensitivity of the polar boundary layer to transient phenomena
Kaiser, A.; Vercauteren, N.; Krumscheid, S.
2024. Nonlinear Processes in Geophysics, 31 (1), 45–60. doi:10.5194/npg-31-45-2024

Discovering Process Dynamics for Scalable Perovskite Solar Cell Manufacturing with Explainable AI
Klein, L.; Ziegler, S.; Laufer, F.; Debus, C.; Götz, M.; Maier-Hein, K.; Paetzold, U. W.; Isensee, F.; Jäger, P. F.
2024. Advanced Materials, 36 (7), Art.-Nr.: 2307160. doi:10.1002/adma.202307160

GPU-resident sparse direct linear solvers for alternating current optimal power flow analysis
Świrydowicz, K.; Koukpaizan, N.; Ribizel, T.; Göbel, F.; Abhyankar, S.; Anzt, H.; Peleš, S.
2024. International Journal of Electrical Power & Energy Systems, 155 (Part A), Art.-Nr.: 109517. doi:10.1016/j.ijepes.2023.109517

Correlation of wall heat loss with quenching distance for premixed H/Air flames during unsteady Flame-Wall interaction
Zhu, J.; Zirwes, T.; Zhang, F. C.; Li, Z. J.; Zhang, Y.; Pan, J. F.
2024. Chemical Engineering Science, 283, 119391. doi:10.1016/j.ces.2023.119391

Rigidity of -harmonic maps of low degree
Hörter, J.; Lamm, T.; Micallef, M.
2023. Annali della Scuola Normale Superiore di Pisa - Classe di Scienze, 24 (4), 2269 – 2310. doi:10.2422/2036-2145.202201_002

Computergestützte Analyse von Illustrationswiederverwendungen in deutschsprachigen Drucken des 16. Jahrhunderts. Am Beispiel Frankfurt am Main. Dissertation
Götzelmann, G.
2023, Dezember 21. doi:10.26083/tuprints-00026365

A parallel-in-time collocation method using diagonalization: theory and implementation for linear problems
Čaklović, G.; Speck, R.; Frank, M.
2023. Communications in Applied Mathematics and Computational Science, 18 (1), 55 – 85. doi:10.2140/camcos.2023.18.55

Towards a Benchmark Dataset for the Digital Humanities
Ernst, F.; Blumenröhr, N.
2023. OM 2023 Ontology Matching : Proceedings of the 18th International Workshop on Ontology Matching, co-located with the 22nd International Semantic Web Conference (ISWC 2023), Athens, Greece, November 7, 2023. Ed.: P. Shvaiko, 200–202, CEUR-WS

Measurement of Triple-Differential Z+Jet Cross Sections with the CMS Detector at 13 TeV and Modelling of Large-Scale Distributed Computing Systems. Dissertation
Horzela, M. M.
2023, Dezember 14. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000165566

Synchronization-free algorithms for exascale and beyond : A study of Asynchronous and Batched Iterative Methods. Dissertation
Nayak, P. V.
2023, Dezember 13. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000165437

Learning Causal Graphs in Manufacturing Domains Using Structural Equation Models
Kertel, M.; Harmeling, S.; Pauly, M.; Klein, N.
2023. International Journal of Semantic Computing, 17 (04), 511–528. doi:10.1142/S1793351X23630023

Three-precision algebraic multigrid on GPUs
Tsai, Y.-H. M.; Beams, N.; Anzt, H.
2023. Future Generation Computer Systems, 149, 280–293. doi:10.1016/j.future.2023.07.024

An Empirical Analysis of Newcomers’ Contributions to Software-Engineering Conferences
Alchokr, R.; Krüger, J.; Shakeel, Y.; Saake, G.; Leich, T.
2023. Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration – 25th International Conference on Asia-Pacific Digital Libraries, ICADL 2023, Taipei, Taiwan, December 4–7, 2023, Proceedings, Part I. Ed.: D. Goh, 231 – 247, Springer Nature Singapore. doi:10.1007/978-981-99-8085-7_21

Implementation of an InfraStructure for dAta-BasEd Learning in environmental sciences (ISABEL)
Strobl, M.; Azmi, E.; Bischof, B.; Dolich, A.; Hassler, S. K.; Mälicke, M.; Jaseetha, A. M.; Meyer, J.; Streit, A.; Zehe, E.
2023. E-Science-Tage 2023 : Empower Your Research – Preserve Your Data. Hrsg.: V. Heuveline, 295–300, heiBOOKS. doi:10.11588/heibooks.1288.c18091

ParaDiag and Collocation Methods: Theory and Implementation. Dissertation
Caklovic, G.
2023, November 28. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000164518

Porting Batched Iterative Solvers onto Intel GPUs with SYCL
Nguyen, P.; Nayak, P.; Anzt, H.
2023. Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, Denver, USA, 12-17 November 2023, 1048 – 1058, Association for Computing Machinery (ACM). doi:10.1145/3624062.3624181

Parallel Symbolic Cholesky Factorization
Ribizel, T.; Anzt, H.
2023. Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, Denver, USA, 12-17 November 2023, 1721 – 1727, Association for Computing Machinery (ACM). doi:10.1145/3624062.3624253

Semantic Segmentation of Crops and Weeds with Probabilistic Modeling and Uncertainty Quantification
Celikkan, E.; Saberioon, M.; Herold, M.; Klein, N.
2023. Proceedings of the IEEE/CVF International Conference on Computer Vision, Paris, 2nd - 6th October 2023, 582–592, IEEEXplore. doi:10.1109/ICCVW60793.2023.00065

Accounting for time dependency in meta‐analyses of concordance probability estimates
Schmid, M.; Friede, T.; Klein, N.; Weinhold, L.
2023. Research Synthesis Methods, 14 (6), 807–823. doi:10.1002/jrsm.1655

Deep learning based automated delineation of the intraprostatic gross tumour volume in PSMA-PET for patients with primary prostate cancer
Holzschuh, J. C.; Mix, M.; Ruf, J.; Hölscher, T.; Kotzerke, J.; Vrachimis, A.; Doolan, P.; Ilhan, H.; Marinescu, I. M.; Spohn, S. K. B.; Fechter, T.; Kuhn, D.; Bronsert, P.; Gratzke, C.; Grosu, R.; u. a.
2023. Radiotherapy and Oncology, 188, Art.-Nr.: 109774. doi:10.1016/j.radonc.2023.109774

Deep-Learning-Based 3-D Surface Reconstruction—A Survey
Farshian, A.; Götz, M.; Cavallaro, G.; Debus, C.; Nießner, M.; Benediktsson, J. A.; Streit, A.
2023. Proceedings of the IEEE, 111 (11), 1464 – 1501. doi:10.1109/JPROC.2023.3321433

Novel Approach for Passive Mixing in Microfluidics Utilizing Porous PDMS Sponge
Grigorov, E.; Kirov, B.; Denev, J. A.; Galabov, V.
2023. 2023 International Scientific Conference on Computer Science (COMSCI), Sozopol, 18th-20th September 2023, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/COMSCI59259.2023.10315880

Search for the Higgs boson decay to a pair of electrons in proton-proton collisions at = 13 TeV
Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; u. a.
2023. Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics, 846, Art.-Nr.: 137783. doi:10.1016/j.physletb.2023.137783

Improving volume-averaged simulations of matrix-stabilized combustion through direct X-ray µCT characterization: Application to NH₃/H₂-air combustion
Zirwes, T.; Vignat, G.; Toro, E. R.; Boigné, E.; Younes, K.; Trimis, D.; Ihme, M.
2023. Combustion and Flame, 257 (2), Article no: 113020. doi:10.1016/j.combustflame.2023.113020

KiT-RT: An extendable framework for radiative transfer and therapy
Kusch, J.; Schotthöfer, S.; Stammer, P.; Wolters, J.; Xiao, T.
2023. ACM Transactions on Mathematical Software, 49 (4), Art.-Nr.: 38. doi:10.1145/3630001

Designing a Mobility Data Trustee (MDT) – Findings From a Multi-Disciplinary Analysis of Requirements of an MDT
Czech, A.; Geenen, V.; Breß, C.; Turkovic Popovski, M.; Krauß, P.; Riedel, T.; Gauterin, F.
2023. Proceedings of the Conference on Research Data Infrastructure, 1, Article no: 64. doi:10.52825/cordi.v1i.370

VπLES- hybrid vortex and grid based method for simulation of turbulent flows at high Re numbers
Kornev, N.; Darji, J.; Tofighian, H.; Denev, J. A.
2023. Proceedings of the 10th International Conference on Vortex Flow Mechanics (ICVFM 2023)

Improvement of temperature uniformity by using novel guide vanes in solar external receiver tubes
Long, Y.; Tu, Z.; Piccioni Koch, D.; Frank, M.; Zhu, R.
2023. Applied Thermal Engineering, 233, Art.-Nr.: 121182. doi:10.1016/j.applthermaleng.2023.121182

RelaxNet: A structure-preserving neural network to approximate the Boltzmann collision operator
Xiao, T.; Frank, M.
2023. Journal of Computational Physics, 490, Art.-Nr.: 112317. doi:10.1016/j.jcp.2023.112317

Boosting Distributional Copula Regression
Hans, N.; Klein, N.; Faschingbauer, F.; Schneider, M.; Mayr, A.
2023. Biometrics, 79 (3), 2298–2310. doi:10.1111/biom.13765

Der krönende Abschluss: Paläographische Besonderheiten im Kontext der automatischen Texterkennung
Frank, L.; Ernst, F.; Götzelmann, G.
2023. P. Helling, P. Gietz & M. Derntl (Hrsg.), FORGE 2023 - Forschungsdaten in den Geisteswissenschaften: Anything Goes?! Forschungsdaten in den Geisteswissenschaften - kritisch betrachtet. Konferenzabstracts, Ed.: M. Derntl. doi:10.5281/zenodo.8386432

EVOKS - Benutzerfreundliche Erstellung kontrollierter Vokabulare für die Geisteswissenschaften
Ernst, F.; Frank, L.; Götzelmann, G.; Eckhardt, K.; Maly, J.; Preker, Y.; Scholz, J.
2023. P. Helling, P. Gietz & M. Derntl (Hrsg.), FORGE 2023 - Forschungsdaten in den Geisteswissenschaften: Anything Goes?! Forschungsdaten in den Geisteswissenschaften - kritisch betrachtet. Konferenzabstracts, Ed.: M. Derntl. doi:10.5281/zenodo.8386468

Inverse design of all-dielectric metasurfaces with accidental bound states in the continuum
Gladyshev, S.; Karamanos, T. D.; Kuhn, L.; Beutel, D.; Weiss, T.; Rockstuhl, C.; Bogdanov, A.
2023. Nanophotonics, 12 (19), 3767–3779. doi:10.1515/nanoph-2023-0373

Proton reconstruction with the CMS-TOTEM Precision Proton Spectrometer
Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; u. a.
2023. Journal of Instrumentation, 18 (09), P09009. doi:10.1088/1748-0221/18/09/P09009

Farm structure and environmental context drive farmers’ decisions on the spatial distribution of ecological focus areas in Germany
Alarcón-Segura, V.; Roilo, S.; Paulus, A.; Beckmann, M.; Klein, N.; Cord, A. F.
2023. Landscape Ecology, 38 (9), 2293–2305. doi:10.1007/s10980-023-01709-8

A numerical study of a cold-mode fluidized bed reactor designed for pyrolysis of plastics
Zhang, F.; Tavakkol, S.; Dercho, S.; Bohlender, L.; Zirwes, T.; Zeller, M.; Vogt, J.; Stapf, D.
2023. 31. Deutscher Flammentag für Nachhaltige Verbrennung 2023, Berlin, 27. und 28. September 2023

An assessment of fluidized bed dynamics with CPFD simulations
Zhang, F.; Tavakkol, S.; Bohlender, L.; Dercho, S.; Zirwes, T.; Zeller, M.; Vogt, J.; Stapf, D.
2023. 31. Deutscher Flammentag

Predicting continuum breakdown with deep neural networks
Xiao, T.; Schotthöfer, S.; Frank, M.
2023. Journal of Computational Physics, 489, Art.-Nr.: 112278. doi:10.1016/j.jcp.2023.112278

From implementation to application: FAIR digital objects for training data composition
Blumenröhr, N.; Aversa, R.
2023. Research Ideas and Outcomes, 9, e108706. doi:10.3897/rio.9.e108706

Providing AI expertise as an infrastructure in academia
Piraud, M.; Camero, A.; Götz, M.; Kesselheim, S.; Steinbach, P.; Weigel, T.
2023. Patterns, 4 (8), Art.-Nr.: 100819. doi:10.1016/j.patter.2023.100819

Constraints on anomalous Higgs boson couplings to vector bosons and fermions from the production of Higgs bosons using the τ τ final state
Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Frühwirth, R.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; u. a.
2023. Physical Review D, 108 (3), 032013. doi:10.1103/PhysRevD.108.032013

A survey of the European Open Science Cloud services for expanding the capacity and capabilities of multidisciplinary scientific applications
Calatrava, A.; Asorey, H.; Astalos, J.; Azevedo, A.; Benincasa, F.; Blanquer, I.; Bobak, M.; Brasileiro, F.; Codó, L.; del Cano, L.; Esteban, B.; Ferret, M.; Handl, J.; Kerzenmacher, T.; Kozlov, V.; u. a.
2023. Computer Science Review, 49, Artkl.Nr.: 100571. doi:10.1016/j.cosrev.2023.100571

Integrating batched sparse iterative solvers for the collision operator in fusion plasma simulations on GPUs
Kashi, A.; Nayak, P.; Kulkarni, D.; Scheinberg, A.; Lin, P.; Anzt, H.
2023. Journal of Parallel and Distributed Computing, 178, 69–81. doi:10.1016/j.jpdc.2023.03.012

Soiling determination for parabolic trough collectors based on operational data analysis and machine learning
Brenner, A.; Kahn, J.; Hirsch, T.; Röger, M.; Pitz-Paal, R.
2023. Solar Energy, 259, 257–276. doi:10.1016/j.solener.2023.05.008

Approximate Bayesian Computation for Parameter Identification in Computational Mechanics
Faes, M. G. R.; Klein, N.; Pauly, M.; Valdebenito, M. A.; Misraji, M. A.
2023. 14th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP14, Dublin, Ireland, July 9-13, 2023, 1–7

Search for a massive scalar resonance decaying to a light scalar and a Higgs boson in the four b quarks final state with boosted topology
Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Frühwirth, R.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; u. a.
2023. Physics Letters B, 842, Art.-Nr.: 137392. doi:10.1016/j.physletb.2022.137392

Modelling the response of a turbulent jet flame to acoustic forcing in a linearized framework using an active flame approach
Kaiser, T. L.; Varillon, G.; Polifke, W.; Zhang, F.; Zirwes, T.; Bockhorn, H.; Oberleithner, K.
2023. Combustion and Flame, 253, Art.-Nr.: 112778. doi:10.1016/j.combustflame.2023.112778

Marginally calibrated response distributions for end-to-end learning in autonomous driving
Hoffmann, C.; Klein, N.
2023. The Annals of Applied Statistics, 17 (2), 1740–1763. doi:10.1214/22-AOAS1693

Computational Studies of Transmembrane Proteins. Dissertation
Kumar, D.
2023, Juni 30. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000152704

Enhancing Multi-Scale Simulations of Charge and Exciton Transfer with Machine Learning Methods. Dissertation
Dohmen, P. M.
2023, Juni 29. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000156196

Applying Metadata Management: Extraction, Mapping & Visualisation
Abdildina, G.; Heinrichs, B.; Joseph, R. E.; Kirar, A.; Vitali, E. G. G.; Aversa, R.
2023

Approximation and Optimization of Global Environmental Simulations with Neural Networks
Azmi, E.; Meyer, J.; Strobl, M.; Weimer, M.; Streit, A.
2023. PASC ’23: Proceedings of the Platform for Advanced Scientific Computing Conference Platform for Advanced Scientific Computing Conference (2023) Davos, Schweiz, 26.06.2023–28.06.2023, Art.-Nr.: 19, Association for Computing Machinery (ACM). doi:10.1145/3592979.3593418

Unraveling the effect of hydrogenation on the mechanical properties of coiled carbon nanotubes: a molecular dynamics study
Saray, M. A.; Baghani, M.; Rajabpour, A.; Sharifian, A.; Baniassadi, M.
2023. Physical Chemistry Chemical Physics, 25 (23), 15988–16000. doi:10.1039/D3CP00894K

Synergies between Numerical Methods for Kinetic Equations and Neural Networks. Dissertation
Schotthöfer, S.
2023, Juni 5. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000158838

Deep distributional time series models and the probabilistic forecasting of intraday electricity prices
Klein, N.; Smith, M. S.; Nott, D. J.
2023. Journal of Applied Econometrics, 38 (4), 493–511. doi:10.1002/jae.2959

Maschinelles Lernen im Schulunterricht am Beispiel einer problemorientierten Lerneinheit zur Wortvorhersage
Hofmann, S.; Frank, M.
2023. 56. Jahrestagung der Gesellschaft für Didaktik der Mathematik, 157–160, WTM Verlag für wissenschaftliche Texte und Medien. doi:10.17877/DE290R-23317

MSLE: An ontology for materials science laboratory equipment – Large-scale devices for materials characterization
Jalali, M.; Mail, M.; Aversa, R.; Kübel, C.
2023. Materials Today Communications, 35, Art.-Nr.: 105532. doi:10.1016/j.mtcomm.2023.105532

The Three-Phase Contact Potential Difference Modulates the Water Surface Charge
Artemov, V.; Frank, L.; Doronin, R.; Stärk, P.; Schlaich, A.; Andreev, A.; Leisner, T.; Radenovic, A.; Kiselev, A.
2023. The Journal of Physical Chemistry Letters, 14 (20), 4796–4802. doi:10.1021/acs.jpclett.3c00479

Improvements of the Density-Functional Tight-Binding Parameters and Their Application in Histidine Kinase. Dissertation
Kansari, M.
2023, Mai 25. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000155207

Boosting multivariate structured additive distributional regression models
Strömer, A.; Klein, N.; Staerk, C.; Klinkhammer, H.; Mayr, A.
2023. Statistics in Medicine, 42 (11), 1779–1801. doi:10.1002/sim.9699

Modelling intra-annual tree stem growth with a distributional regression approach for Gaussian process responses
Riebl, H.; Klein, N.; Kneib, T.
2023. Journal of the Royal Statistical Society Series C: Applied Statistics, 72 (2), 414–433. doi:10.1093/jrsssc/qlad015

Uncertainty quantification and numerical methods in charged particle radiation therapy. Dissertation
Stammer, P.
2023, Mai 4. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000158316

CAG-Repeat RNA Hairpin Folding and Recruitment to Nuclear Speckles with a Pivotal Role of ATP as a Cosolute
Hautke, A.; Hautke, A.; Voronin, A.; Idiris, F.; Riel, A.; Lindner, F.; Lelièvre-Büttner, A.; Zhu, J.; Appel, B.; Fatti, E.; Weis, K.; Müller, S.; Schug, A.; Ebbinghaus, S.
2023. Journal of the American Chemical Society, 145 (17), 9571–9583. doi:10.1021/jacs.2c13653

Utilizing batched solver ideas for efficient solution of non-batched linear systems
Nayak, P.; Anzt, H.
2023. 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 662 – 665, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IPDPSW59300.2023.00113

Implicit propagation of directly addressed grids in lattice Boltzmann methods
Kummerländer, A.; Dorn, M.; Frank, M.; Krause, M. J.
2023. Concurrency and Computation: Practice and Experience, 35 (8), Art.-Nr.: e7509. doi:10.1002/cpe.7509

A Flux Reconstruction Stochastic Galerkin Scheme for Hyperbolic Conservation Laws
Xiao, T.; Kusch, J.; Koellermeier, J.; Frank, M.
2023. Journal of Scientific Computing, 95 (1), 18. doi:10.1007/s10915-023-02143-3

Experimental and numerical investigation of flame stabilization and pollutant formation in matrix stabilized ammonia-hydrogen combustion
Vignat, G.; Zirwes, T.; Toro, E. R.; Younes, K.; Boigné, E.; Muhunthan, P.; Simitz, L.; Trimis, D.; Ihme, M.
2023. Combustion and Flame, 250, Article no: 112642. doi:10.1016/j.combustflame.2023.112642

Process Insights into Perovskite Thin‐Film Photovoltaics from Machine Learning with In Situ Luminescence Data
Laufer, F.; Ziegler, S.; Schackmar, F.; Viteri, E. A. M.; Götz, M.; Debus, C.; Isensee, F.; Paetzold, U. W.
2023. Solar RRL, 7 (7), Art.-Nr.: 2201114. doi:10.1002/solr.202201114

Development of a scoring function for comparing simulated and experimental tumor spheroids
Herold, J.; Behle, E.; Rosenbauer, J.; Ferruzzi, J.; Schug, A.
2023. (P. M. Altrock, Hrsg.) PLOS Computational Biology, 19 (3), Art.-Nr. e1010471. doi:10.1371/journal.pcbi.1010471

Schrifttradition digital: Rituell reine Torarollen in der jüdischen Diaspora
Frank, L.; Eichhorst, D.; Ullrich, R.; Haddassah Wendl, K.; Martini, A.; Tonne, D.
2023. DHd2023: Open Humanities, Open Culture. Konferenzabstracts. Hrsg.: A. Busch, 283–286, Zenodo. doi:10.5281/zenodo.7715864

A robust collision source method for rank adaptive dynamical low-rank approximation in radiation therapy
Kusch, J.; Stammer, P.
2023. ESAIM: Mathematical Modelling and Numerical Analysis, 57 (2), 865–891. doi:10.1051/m2an/2022090

Exploiting graph neural networks to perform finite-difference time-domain based optical simulations
Kuhn, L.; Repän, T.; Rockstuhl, C.
2023. APL Photonics, 8 (3), Article no: 036109. doi:10.1063/5.0139004

Impact of carbon dioxide and nitrogen addition on the global structure of hydrogen flames
Eckart, S.; Pio, G.; Zirwes, T.; Zhang, F.; Salzano, E.; Krause, H.; Bockhorn, H.
2023. Fuel, 335, Art.-Nr.: 126929. doi:10.1016/j.fuel.2022.126929

Constructing relaxation systems for lattice Boltzmann methods
Simonis, S.; Frank, M.; Krause, M. J.
2023. Applied Mathematics Letters, 137, Art.-Nr.: 108484. doi:10.1016/j.aml.2022.108484

Machine learning-based conditional mean filter: A generalization of the ensemble Kalman filter for nonlinear data assimilation
Hoang, T.-V.; Krumscheid, S.; Matthies, H. G.; Tempone, R.
2023. Foundations of Data Science, 5, 56–80. doi:10.3934/fods.2022016

Towards cellular digital twins of in vivo tumors
Behle, E.; Herold, J. M.; Schug, A. H.
2023. Biophysical Journal, 122 (3 Supplement 1), 301a–302a. doi:10.1016/j.bpj.2022.11.1700

Using machine learning to parametrize large scale tumor simulations
Herold, J. M.; Behle, E.; Schug, A. H.
2023. Biophysical Journal, 122 (3 Supplement 1), 413a. doi:10.1016/j.bpj.2022.11.2243

Extending the distributed computing infrastructure of the CMS experiment with HPC resources
Adelman-McCarthy, J.; Boccali, T.; Caspart, R.; Delgado Peris, A.; Fischer, M.; Flix Molina, J.; Giffels, M.; Hernández, J. M.; Hufnagel, D.; Kühn, E.; Madlener, T.; Mohapatra, A. K.; Ozturk, H.; Pérez-Calero Yzquierdo, A.; Spiga, D.; u. a.
2023. Journal of Physics: Conference Series, 2438 (1), Artkl.Nr.: 012039. doi:10.1088/1742-6596/2438/1/012039

Deep learning approaches to building rooftop thermal bridge detection from aerial images
Mayer, Z.; Kahn, J.; Hou, Y.; Götz, M.; Volk, R.; Schultmann, F.
2023. Automation in Construction, 146, Art.-Nr.: 104690. doi:10.1016/j.autcon.2022.104690

Modeling of radiation heat transfer in dense-bed flows of solids in indirectly heated rotary kilns
Tavakkol, S.; Zirwes, T.; Denev, J. A.; Bockhorn, H.; Stapf, D.
2023. Thermal Science and Engineering Progress, 38, Article no: 101545. doi:10.1016/j.tsep.2022.101545

Multivariate error modeling and uncertainty quantification using importance (re-)weighting for Monte Carlo simulations in particle transport
Stammer, P.; Burigo, L.; Jäkel, O.; Frank, M.; Wahl, N.
2023. Journal of Computational Physics, 473, Artkel-Nr.: 111725. doi:10.1016/j.jcp.2022.111725

Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads
Caspart, R.; Ziegler, S.; Weyrauch, A.; Obermaier, H.; Raffeiner, S.; Schuhmacher, L. P.; Scholtyssek, J.; Trofimova, D.; Nolden, M.; Reinartz, I.; Isensee, F.; Götz, M.; Debus, C.
2023. High Performance Computing. ISC High Performance 2022 International Workshops – Hamburg, Germany, May 29 – June 2, 2022, Revised Selected Papers. Ed.: H. Anzt, 108–121, Springer International Publishing. doi:10.1007/978-3-031-23220-6_8

Overcoming the Limitations of Localization Uncertainty: Efficient and Exact Non-linear Post-processing and Calibration
Kassem Sbeyti, M.; Karg, M.; Wirth, C.; Nowzad, A.; Albayrak, S.
2023. Machine Learning and Knowledge Discovery in Databases: Research Track – European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part V. Ed.: D. Koutra, 52–68, Springer Nature Switzerland. doi:10.1007/978-3-031-43424-2_4

Boosting Distributional Soft Regression Trees
Umlauf, N.; Seiler, J.; Wetscher, M.; Klein, N.
2023. Proceedings of the 37th International Workshop on Statistical Modelling. Ed.: E. Bergherr, 311–316, Technische Universität Dortmund (TU Dortmund)

Complexity Reduction via Deselection for Boosting Distributional Copula Regression
Strömer, A.; Klein, N.; Staerk, C.; Klinkhammer, H.; Mayr, A.
2023. Proceedings of the 37th International Workshop on Statistical Modelling. Ed.: E. Bergherr, 300–304, Technische Universität Dortmund (TU Dortmund)

Informed Priors for Knowledge Integration in Trajectory Prediction
Schlauch, C.; Klein, N.; Wirth, C.; Klein, N.
2023. D. Koutra (Hrsg.), Machine Learning and Knowledge Discovery in Databases: Research Track : European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part V, Hrsg.: D. Koutra, C. Plant, R. M. Gomez, E. Baralis, F. Bonchi, 392–407, Springer Nature Switzerland. doi:10.1007/978-3-031-43424-2_24

The Consequences of not Completing the Generational Cohort in Estimating Age-at-Menopause
Martins, R.; Sousa, B. de; Kneib, T.; Hohberg, M.; Klein, N.; Duarte, E.; Rodrigues, V.
2023. Proceedings of the 37th International Workshop on Statistical Modelling : July 17-21, 2023, Dortmund, Germany, Ed.: E. Bergherr, A. Groll, A. Mayr, 502–506

A Distributional Regression Approach for Gaussian Process Responses
Kneib, T.; Riebl, H.; Klein, N.
2023. Proceedings of the 37th International Workshop on Statistical Modelling July 17-21, 2023 - Dortmund, Germany. Ed.: E. Bergherr, 279–284, Technische Universität Dortmund (TU Dortmund)

Predicting cycling traffic in cities: Is bikesharing data representative of the cycling volume
Kaiser, S. K.; Klein, N.; Kaack, L. H.
2023. 11th International Conference on Learning Representations (ICLR 2023): Tackling Climate Change with Machine Learning Workshop

deepregression : A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression
Rügamer, D.; Kolb, C.; Fritz, C.; Pfisterer, F.; Kopper, P.; Bischl, B.; Shen, R.; Bukas, C.; Barros de Andrade e Sousa, L.; Thalmeier, D.; Baumann, P. F. M.; Kook, L.; Klein, N.; Müller, C. L.
2023. Journal of Statistical Software, 105 (2). doi:10.18637/jss.v105.i02

perun: Benchmarking Energy Consumption of High-Performance Computing Applications
Gutiérrez Hermosillo Muriedas, J. P.; Flügel, K.; Debus, C.; Obermaier, H.; Streit, A.; Götz, M.
2023. Euro-Par 2023: Parallel Processing. Ed.: J. Cano, 17–31, Springer Nature Switzerland. doi:10.1007/978-3-031-39698-4_2

Reporting electricity consumption is essential for sustainable AI
Debus, C.; Piraud, M.; Streit, A.; Theis, F.; Götz, M.
2023. Nature Machine Intelligence, 5 (11), 1176–1178. doi:10.1038/s42256-023-00750-1

Global sensitivity analysis of a one-dimensional ocean biogeochemical model
Mamnun, N.; Völker, C.; Krumscheid, S.; Vrekoussis, M.; Nerger, L.
2023. Socio-Environmental Systems Modelling, 5, Art.-Nr.: 18613. doi:10.18174/sesmo.18613

Cat4KIT: A Cross-institutional Data Catalog Framework for the FAIRification of Environmental Research Data
Hadizadeh, M.; Lorenz, C.; Barthlott, S.; Fösig, R.; Çayoğlu, U.; Ulrich, R.; Bach, F.
2023. E-Science-Tage 2023. Hrsg.: V. Heuveline, 149–160, heiBOOKS. doi:10.11588/heibooks.1288.c18072

Data Competence for Photonic Nanotechnologies
Meyer, J.; Asadova, N.; Beutel, D.; Çayoğlu, U.; Rockstuhl, C.; Tristram, F.
2023. E-Science-Tage 2023. Empower Your Research – Preserve Your Data. Eds.: Vincent Heuveline, Nina Bisheh und Philipp Kling, 301–305, heiBOOKS. doi:10.11588/heibooks.1288.c18092

Low-Cost Three-Dimensionally Printed Inverted Plug and Play Optical Instrument for Microfluidic Imaging
Markov, D.; Grigorov, E.; Kirov, B.; Denev, J. A.; Galabov, V.; Marinov, M. B.
2023. Micro, 3 (2), 537–548. doi:10.3390/micro3020036

A community‐endorsed open‐source lexicon for contrast agent–based perfusion MRI : A consensus guidelines report from the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI)
on behalf of The Perfusion Study Group of the ISMRM; Dickie, B. R.; Ahmed, Z.; Arvidsson, J.; Bell, L. C.; Buckley, D. L.; Debus, C.; Fedorov, A.; Floca, R.; Gutmann, I.; van der Heijden, R. A.; van Houdt, P. J.; Sourbron, S.; Thrippleton, M. J.; Quarles, C.; u. a.
2023. Magnetic Resonance in Medicine. doi:10.1002/mrm.29840

A search for new physics in central exclusive production using the missing mass technique with the CMS detector and the CMS-TOTEM precision proton spectrometer
CMS and TOTEM Collaborations; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Valle, A. E. D.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; u. a.
2023. The European Physical Journal C, 83 (9), Art - Nr.: 827. doi:10.1140/epjc/s10052-023-11687-5

An iterative methodology for REDIM reduced chemistry generation and its validation for partially-premixed combustion
Shrotriya, P.; Schießl, R.; Yu, C.; Bykov, V.; Zirwes, T.; Maas, U.
2023. Combustion Theory and Modelling, 1–34. doi:10.1080/13647830.2023.2260350

Long Term Interoperability of Distributed Research Data Infrastructures
Politze, M.; Shakeel, Y.; Hunke, S.; Ost, P.; Aversa, R.; Heinrichs, B.; Lang, I.
2023. Proceedings of the Conference on Research Data Infrastructure, 1. doi:10.52825/cordi.v1i.348

Data Collections Explorer – An Easy-to-Use Tool for Sharing and Discovering Research Data
Ost, P.; Shakeel, Y.; Tögel, P.
2023. Proceedings of the Conference on Research Data Infrastructure. Ed.: Y. Sure-Vetter. Vol. 1, 3 S., Technische Informationsbibliothek Open Publishing (TIB Open Publishing). doi:10.52825/cordi.v1i.405

RNA contact prediction by data efficient deep learning
Taubert, O.; von der Lehr, F.; Bazarova, A.; Faber, C.; Knechtges, P.; Weiel, M.; Debus, C.; Coquelin, D.; Basermann, A.; Streit, A.; Kesselheim, S.; Götz, M.; Schug, A.
2023. Communications Biology, 6 (1), 913. doi:10.1038/s42003-023-05244-9

Sparse matrix‐vector and matrix‐multivector products for the truncated SVD on graphics processors
Aliaga, J. I.; Anzt, H.; Quintana-Ortí, E. S.; Tomás, A. E.
2023. Concurrency and Computation: Practice and Experience, 35 (28), Art.-Nr.: e7871. doi:10.1002/cpe.7871

Collaboration through reuse: Analyzing letters explored by others
Tögel, P.
2023. Digital Humanities 2023: Book of Abstracts. Ed.: A. Baillot, 471–472, Zenodo. doi:10.5281/zenodo.8108012

Search for light Higgs bosons from supersymmetric cascade decays in collisions at
CMS Collaboration; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Valle, A. E. D.; Frühwirth, R.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; u. a.
2023. The European Physical Journal C, 83 (7), Art.-Nr.: 571. doi:10.1140/epjc/s10052-023-11581-0

Measurement of the differential production cross section as a function of the jet mass and extraction of the top quark mass in hadronic decays of boosted top quarks
CMS Collaboration; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Valle, A. E. D.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; u. a.
2023. The European Physical Journal C, 83 (7), Art.-Nr.: 560. doi:10.1140/epjc/s10052-023-11587-8

Assessment of Numerical Accuracy and Parallel Performance of OpenFOAM and its Reacting Flow Extension EBIdnsFoam
Zirwes, T.; Sontheimer, M.; Zhang, F.; Abdelsamie, A.; Pérez, F. E. H.; Stein, O. T.; Im, H. G.; Kronenburg, A.; Bockhorn, H.
2023. Flow, Turbulence and Combustion, 111 (2), 567–602. doi:10.1007/s10494-023-00449-8

Mixed Precision Algebraic Multigrid on GPUs
Tsai, Y.-H. M.; Beams, N.; Anzt, H.
2023. Parallel Processing and Applied Mathematics – 14th International Conference, PPAM 2022, Gdansk, Poland, September 11–14, 2022, Revised Selected Papers, Part I. Ed.: R. Wyrzykowski, 113 – 125, Springer International Publishing. doi:10.1007/978-3-031-30442-2_9

Massively Parallel Genetic Optimization Through Asynchronous Propagation of Populations
Taubert, O.; Weiel, M.; Coquelin, D.; Farshian, A.; Debus, C.; Schug, A.; Streit, A.; Götz, M.
2023. High Performance Computing – 38th International Conference, ISC High Performance 2023, Hamburg, Germany, May 21–25, 2023, Proceedings. Ed.: A. Bhatele, 106 – 124, Springer Nature Switzerland. doi:10.1007/978-3-031-32041-5_6

A Mixed Precision Randomized Preconditioner for the LSQR Solver on GPUs
Georgiou, V.; Boutsikas, C.; Drineas, P.; Anzt, H.
2023. High Performance Computing – 38th International Conference, ISC High Performance 2023, Hamburg, Germany, May 21–25, 2023, Proceedings. Ed.: A. Bhatele, 164 – 181, Springer Nature Switzerland. doi:10.1007/978-3-031-32041-5_9

FAIR Data Management Workflow for MRI Data
Aversa, R.; MacKinnon, N.; Blumenröhr, N.
2023. 3rd Workshop on Metadata and Research (objects) Management for Linked Open Science (DaMaLOS 2023) - Co-located with Extended Semantic Web Conference (ESWC), Online, 28.-29.05.2023, paper 5349. doi:10.4126/FRL01-006444992

Klassifizierungsprobleme : Maschinelles Lernen und KI im Mathematikunterricht
Schönbrodt, S.; Frank, M.
2023. Beiträge zum Mathematikunterricht 2022, Gesellschaft für Didaktik der Mathematik (GDM). doi:10.17877/DE290R-23426

Sp(2N) Lattice Gauge Theories and Extensions of the Standard Model of Particle Physics
Bennett, E.; Holligan, J.; Hong, D. K.; Hsiao, H.; Lee, J.-W.; Lin, C.-J. D.; Lucini, B.; Mesiti, M.; Piai, M.; Vadacchino, D.
2023. Universe, 9 (5), Art.-Nr.: 236. doi:10.3390/universe9050236

Quantifying uncertain system outputs via the multi-level Monte Carlo method --- distribution and robustness measures
Ayoul-Guilmard, Q.; Ganesh, S.; Krumscheid, S.; Nobile, F.
2023. International Journal for Uncertainty Quantification, 13 (5), 61–98. doi:10.1615/Int.J.UncertaintyQuantification.2023045259

Thermal Bridges on Building Rooftops
Mayer, Z.; Kahn, J.; Götz, M.; Hou, Y.; Beiersdörfer, T.; Blumenröhr, N.; Volk, R.; Streit, A.; Schultmann, F.
2023. Scientific Data, 10 (1), Art.-Nr.: 268. doi:10.1038/s41597-023-02140-z

Effect of nozzle up-scaling on coaxial, gas-assisted atomization
Zhang, F.; Wachter, S.; Zirwes, T.; Jakobs, T.; Zarzalis, N.; Trimis, D.; Kolb, T.; Stapf, D.
2023. Physics of Fluids, 35 (4), Art.-Nr.: 043302. doi:10.1063/5.0141156

Isotopic measurements in water vapor, precipitation, and seawater during EURECA
Bailey, A.; Aemisegger, F.; Villiger, L.; Los, S. A.; Reverdin, G.; Quiñones Meléndez, E.; Acquistapace, C.; Baranowski, D. B.; Böck, T.; Bony, S.; Bordsdorff, T.; Coffman, D.; de Szoeke, S. P.; Diekmann, C. J.; Dütsch, M.; u. a.
2023. Earth System Science Data, 15 (1), 465–495. doi:10.5194/essd-15-465-2023

Multiscale Modeling of Spheroid Tumors: Effect of Nutrient Availability on Tumor Evolution
Rosenbauer, J.; Berghoff, M.; Glazier, J. A.; Schug, A.
2023. The Journal of Physical Chemistry B, 127 (16), 3607–3615. doi:10.1021/acs.jpcb.2c08114

Peer-Reviewing and Submission Dynamics Around Top Software-Engineering Venues: A Juniors’ Perspective
Alchokr, R.; Krüger, J.; Shakeel, Y.; Saake, G.; Leich, T.
2023. T. M. Engels G. Hebig R. (Hrsg.), Software Engineering 2023 Ed.: G. Engels, 31–32, Gesellschaft für Informatik (GI)

Training Parameterized Quantum Circuits with Triplet Loss
Wendenius, C.; Kuehn, E.; Streit, A.
2023. Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings. Part V. Ed.: M.-R. Amini, 515–530, Springer Nature Switzerland. doi:10.1007/978-3-031-26419-1_31

Metaphors of Religion
Gebhard, H.; Jha, V.; Tögel, P.; Dipper, S.; Elwert, F.; Tonne, D.
2023. DHd2023: Open Humanities, Open Culture. Konferenzabstracts. Hrsg.: A. Busch, 399–401, Zenodo. doi:10.5281/zenodo.7715325

Numerical simulations of air-assisted primary atomization at different air-to-liquid injection angles
Zhang, F.; Zirwes, T.; Wachter, S.; Jakobs, T.; Habisreuther, P.; Zarzalis, N.; Trimis, D.; Kolb, T.; Bockhorn, H.; Stapf, D.
2023. International journal of multiphase flow, 158, Art.-Nr.: 104304. doi:10.1016/j.ijmultiphaseflow.2022.104304

Near-wall dynamics of premixed methane/air flames
Zhu, J.; Pan, J.; Zhang, F.; Zirwes, T.; Ojo, A. O.; Li, F.
2023. Fuel, 331, Art.Nr. 125774. doi:10.1016/j.fuel.2022.125774

Using Ginkgo’s memory accessor for improving the accuracy of memory-bound low precision BLAS
Grützmacher, T.; Anzt, H.; Quintana-Ortí, E. S.
2023. Software - Practice and Experience, 531 (1), 81–98. doi:10.1002/spe.3041

Statistical Learning of Nonlinear Stochastic Differential Equations from Nonstationary Time Series using Variational Clustering
Boyko, V.; Krumscheid, S.; Vercauteren, N.
2022. Multiscale Modeling & Simulation, 20 (4), 1251–1283. doi:10.1137/21M1403989

Is age at menopause decreasing? – The consequences of not completing the generational cohort
Martins, R.; Sousa, B. de; Kneib, T.; Hohberg, M.; Klein, N.; Duarte, E.; Rodrigues, V.
2022. BMC Medical Research Methodology, 22 (1), Art.-Nr. 187. doi:10.1186/s12874-022-01658-x

A low-rank power iteration scheme for neutron transport criticality problems
Kusch, J.; Whewell, B.; Whewell, B.; McClarren, R.
2022. Journal of Computational Physics, 470, 111587. doi:10.1016/j.jcp.2022.111587

A Computational Workflow for Interdisciplinary Deep Learning Projects utilizing bwHPC Infrastructure
Schilling, M.; Neumann, O.; Scherr, T.; Cui, H.; Popova, A. A.; Levkin, P. A.; Götz, M.; Reischl, M.
2022. Proceedings of the 7th bwHPC Symposium, 69–74, Kommunikations- und Informationszentrum (kiz). doi:10.18725/OPARU-46069

Dynamical stability indicator based on autoregressive moving-average models: Critical transitions and the Atlantic meridional overturning circulation
Rodal, M.; Krumscheid, S.; Madan, G.; Henry LaCasce, J.; Vercauteren, N.
2022. Chaos: An Interdisciplinary Journal of Nonlinear Science, 32 (11), Art.-Nr.: 113139. doi:10.1063/5.0089694

Correlated Coevolving Mutations at Protein–Protein Interfaces
Schug, A.
2022. Protein Interactions – The Molecular Basis of Interactomics. Ed.: V. Helms, 39–52, John Wiley and Sons. doi:10.1002/9783527830503.ch3

Implementing Asynchronous Jacobi Iteration on GPUs
Tsai, Y.-H. M.; Nayak, P.; Chow, E.; Anzt, H.
2022. 2022 IEEE/ACM Workshop on Latest Advances in Scalable Algorithms for Large-Scale Heterogeneous Systems (ScalAH). IEEE/ACM Workshop on Latest Advances in Scalable Algorithms for Large-Scale Heterogeneous Systems (ScalAH 2022) Dallas, TX, USA, 13.11.2022–18.11.2022, 1–9, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ScalAH56622.2022.00006

Numerical analysis of a developing turbulent flow and conjugate heat transfer for molten salt and liquid sodium in a solar receiver
Khuda, M. A.; Khalesi, J.; Tu, Z.; Long, Y.; Piccioni Koch, D.; Sarunac, N.
2022. Applied Thermal Engineering, 217, Art.-Nr.: 119156. doi:10.1016/j.applthermaleng.2022.119156

Methodisch-didaktische Entwicklung und Evaluation von interaktiven Lehr- und Lernmaterialien zur Mathematik im Bereich der Klimaforschung. Dissertation
Hattebuhr, M.
2022, Oktober 21. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000151547

FAIR Digital Object Application Case for Composing Machine Learning Training Data
Blumenröhr, N.; Jejkal, T.; Pfeil, A.; Stotzka, R.
2022. Research Ideas and Outcomes, 8, Art.-Nr.: e94113. doi:10.3897/rio.8.e94113

A non-stationary model for spatially dependent circular response data based on wrapped Gaussian processes
Marques, I.; Kneib, T.; Klein, N.
2022. Statistics and Computing, 32 (5), Art.-Nr. 73. doi:10.1007/s11222-022-10136-9

Variational inference and sparsity in high-dimensional deep Gaussian mixture models
Kock, L.; Klein, N.; Nott, D. J.
2022. Statistics and Computing, 32 (5), Art.-Nr. 70. doi:10.1007/s11222-022-10132-z

Flame-vortex interaction during turbulent side-wall quenching and its implications for flamelet manifolds
Steinhausen, M.; Zirwes, T.; Ferraro, F.; Scholtissek, A.; Bockhorn, H.; Hasse, C.
2022. Proceedings of the Combustion Institute, 39 (2), 2149–2158. doi:10.1016/j.proci.2022.09.026

Hyde: The First Open-Source, Python-Based, Gpu-Accelerated Hyperspectral Denoising Package
Coquelin, D.; Rasti, B.; Gotz, M.; Ghamisi, P.; Gloaguen, R.; Streit, A.
2022. 2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), Rome, Italy, 13-16 September 2022, 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/WHISPERS56178.2022.9955088

Learning tree structures from leaves for particle decay reconstruction
Kahn, J.; Tsaklidis, I.; Taubert, O.; Reuter, L.; Dujany, G.; Boeckh, T.; Thaller, A.; Goldenzweig, P.; Bernlochner, F.; Streit, A.; Götz, M.
2022. Machine Learning: Science and Technology, 3 (3), Art.Nr. 035012. doi:10.1088/2632-2153/ac8de0

Measurements and Modelling of Total Ozone Columns near St. Petersburg, Russia
Nerobelov, G.; Timofeyev, Y.; Virolainen, Y.; Polyakov, A.; Solomatnikova, A.; Poberovskii, A.; Kirner, O.; Al-Subari, O.; Smyshlyaev, S.; Rozanov, E.
2022. Remote Sensing, 14 (16), 3944. doi:10.3390/rs14163944

Mitigating spatial confounding by explicitly correlating Gaussian random fields
Marques, I.; Kneib, T.; Klein, N.
2022. Environmetrics, 33 (5), Art.-Nr. e2727. doi:10.1002/env.2727

Effects of low-temperature chemical reactions on ignition kernel development and flame propagation in a DME-air mixing layer
Wang, Y.; Han, W.; Zirwes, T.; Zhang, F.; Bockhorn, H.; Chen, Z.
2022. Proceedings of the Combustion Institute, 39 (2), 1515–1524. doi:10.1016/j.proci.2022.07.024

Multiscale Molecular Dynamics Simulations of Histidine Kinase Activity. Dissertation
Idiris, F.
2022, Juni 29. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000147727

Structures of Small Platinum Cluster Anions Pt: Experiment and Theory
Bumüller, D.; Yohannes, A. G.; Kohaut, S.; Kondov, I.; Kappes, M. M.; Fink, K.; Schooss, D.
2022. The Journal of Physical Chemistry A, 126 (22), 3502–3510. doi:10.1021/acs.jpca.2c02142

Enhanced sampling methods applied to chemical reactions in proteins. Dissertation
Maag, D. M.
2022, Juni 7. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000146741

Application and Optimization of Contact-Guided Replica Exchange Molecular Dynamics. Dissertation
Voronin, A.
2022, Mai 19. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000146554

Ginkgo—A math library designed for platform portability
Cojean, T.; Tsai, Y.-H. M.; Anzt, H.
2022. Parallel Computing, 111, Art.-Nr.: 102902. doi:10.1016/j.parco.2022.102902

V-FOR-WaTer - a virtual research environment for environmental research
Strobl, M.; Azmi, E.; Hassler, S. K.; Mälicke, M.; Meyer, J.; Streit, A.; Zehe, E.
2022. E-Science-Tage 2021: Share Your Research Data. Hrsg.: V. Heuveline, 394–398, Heidelberger E-Books (heiBOOKS). doi:10.11588/heibooks.979.c13755

Modeling of radiation heat transfer in the dense-bed flow of solid pyrolysis in indirectly heated rotary kilns
Tavakkol, S.
2022. Proceedings of the 13th European Conference on Industrial Furnaces and Boilsers (INFUB)

Selection of representative structures from large biomolecular ensembles
Voronin, A.; Schug, A.
2022. The Journal of Chemical Physics, 156 (14), Art.-Nr.: 144102. doi:10.1063/5.0082444

Mathematische Modellierungswochen – auch online
Schönbrodt, S.; Hofmann, S.
2022. Mitteilungen der Deutschen Mathematiker-Vereinigung, 30 (1), 46–50. doi:10.1515/dmvm-2022-0016

Numerical Study on Flame Stabilization and NO Formation in a Novel Burner System for Sulfur Combustion
Zhang, F.; Kurjata, M.; Sebbar, N.; Zirwes, T.; Fedoryk, M.; Harth, S.; Wang, R.; Habisreuther, P.; Trimis, D.; Bockhorn, H.
2022. Energy and Fuels, 36 (7), 4094–4106. doi:10.1021/acs.energyfuels.1c04007

Correcting for sample selection bias in Bayesian distributional regression models
Wiemann, P. F. V.; Klein, N.; Kneib, T.
2022. Computational Statistics & Data Analysis, 168, 107382. doi:10.1016/j.csda.2021.107382

Evaluation of Application Possibilities for Packaging Technologies in Canonical Workflows
Jejkal, T.; Chelbi, S.; Pfeil, A.; Wittenburg, P.
2022. Data Intelligence, 4 (2), 372–385. doi:10.1162/dint_a_00137

Flame structure analysis and composition space modeling of thermodiffusively unstable premixed hydrogen flames. Part II. Elevated pressure
Wen, X.; Zirwes, T.; Scholtissek, A.; Böttler, H.; Zhang, F.; Bockhorn, H.; Hasse, C.
2022. Combustion and Flame, 238, Art.Nr. 111808. doi:10.1016/j.combustflame.2021.111808

Flame structure analysis and composition space modeling of thermodiffusively unstable premixed hydrogen flames. Part I. Atmospheric pressure
Wen, X.; Zirwes, T.; Scholtissek, A.; Böttler, H.; Zhang, F.; Bockhorn, H.; Hasse, C.
2022. Combustion and Flame, 238, Art.Nr. 111815. doi:10.1016/j.combustflame.2021.111815

SmartAQnet 2020: A New Open Urban Air Quality Dataset from Heterogeneous PM Sensors
Li, C.; Budde, M.; Tremper, P.; Schäfer, K.; Riesterer, J.; Redelstein, J.; Petersen, E.; Khedr, M.; Liu, X.; Köpke, M.; Hussain, S.; Ernst, F.; Kowalski, M.; Pesch, M.; Werhahn, J.; u. a.
2022. ProScience, 8. doi:10.14644/dust2021.001

Die Aktualität des Unzeitgemäßen
Krewet, M.; Ernst, F.; Götzelmann, G.; Hegel, P.; Schenk, T.; Söring, S.; Tonne, D.
2022. DHd2022: Kulturen des digitalen Gedächtnisses. Konferenzabstracts, Hrsg: M. Geierhos, 75–78. doi:10.5281/zenodo.6328015

Optimierungsprobleme in der mathematischen Modellierung : Grundlegende Aspekte und Chancen aus Sicht der Mathematikdidaktik – herausgestellt an aktuellen Problemen aus der Forschung zu künstlicher Intelligenz und erneuerbaren Energien. Dissertation
Schönbrodt, S.
2022, März 10. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000143530

Multivariate conditional transformation models
Klein, N.; Hothorn, T.; Barbanti, L.; Kneib, T.
2022. Scandinavian Journal of Statistics, 49 (1), 116–142. doi:10.1111/sjos.12501

Dynamic Provision of Heterogeneous Computing Resources for Computation- and Data-intensive Particle Physics Analyses. Dissertation
Schnepf, M. J.
2022, Februar 28. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000143165

RNA structure prediction with direct coupling analysis
Faber, C.; Bayou Zerihun, M.; Schug, A. H.
2022. Biophysical Journal, 121 (3), 204a. doi:10.1016/j.bpj.2021.11.1695

Machine learning based optimization to simulate tumor development
Herold, J. M.; Behle, E.; Schug, A. H.
2022. Biophysical Journal, 121 (3), 123a. doi:10.1016/j.bpj.2021.11.2100

Cellular ATP levels are paramount for governing stability and LLPS of CAG repeat-containing RNAs inside cell
Hautke, A.; Voronin, A.; Idiris, F.; Schug, A. H.; Ebbinghaus, S.
2022. Biophysical Journal, 121 (3), 311a. doi:10.1016/j.bpj.2021.11.1202

Large-scale simulation of tumor spheroid invasion dynamics
Behle, E.; Herold, J.; Rosenbauer, J.; Schug, A. H.
2022. Biophysical Journal, 121 (3), 165a. doi:10.1016/j.bpj.2021.11.1907

Using biomolecular simulations to interpret experimental data
Schug, A. H.
2022. Biophysical Journal, 121 (3), 321a. doi:10.1016/j.bpj.2021.11.1151

Resolvent-based modelling of coherent structures in a turbulent jet flame using a passive flame approach
Casel, M.; Oberleithner, K.; Zhang, F.; Zirwes, T.; Bockhorn, H.; Trimis, D.; Kaiser, T. L.
2022. Combustion and Flame, 236, Art.-Nr.: 111695. doi:10.1016/j.combustflame.2021.111695

Search for flavor-changing neutral current interactions of the top quark and the Higgs boson decaying to a bottom quark-antiquark pair at = 13 TeV
The CMS collaboration; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Frühwirth, R.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; u. a.
2022. Journal of High Energy Physics, 2022 (2), 169. doi:10.1007/JHEP02(2022)169

Accelerating neural network training with distributed asynchronous and selective optimization (DASO)
Coquelin, D.; Debus, C.; Götz, M.; Lehr, F. von der; Kahn, J.; Siggel, M.; Streit, A.
2022. Journal of Big Data, 9 (1), 14. doi:10.1186/s40537-021-00556-1

Review of guidance papers on regression modeling in statistical series of medical journals
Wallisch, C.; Bach, P.; Hafermann, L.; Klein, N.; Sauerbrei, W.; Steyerberg, E. W.; Heinze, G.; Rauch, G.
2022. (T. Mathes, Hrsg.) PLOS ONE, 17 (1), Art.-Nr.: e0262918. doi:10.1371/journal.pone.0262918

Using Background Knowledge from Preceding Studies for Building a Random Forest Prediction Model: A Plasmode Simulation Study
Hafermann, L.; Klein, N.; Rauch, G.; Kammer, M.; Heinze, G.
2022. Entropy, 24 (6), 847. doi:10.3390/e24060847

Structure Preserving Neural Networks: A Case Study in the Entropy Closure of the Boltzmann Equation
Schotthöfer, S.; Xiao, T.; Frank, M.; Hauck, C.
2022. 39th International Conference on Machine Learning, ICML 2022 Baltimore17 July 2022through 23 July 2022. Ed.: K. Chaudhuri, 19406–19433

Neue Materialien für einen realitätsbezogenen Mathematikunterricht 9 – ISTRON-Schriftenreihe
Frank, M.; Roeckerath, C. (Hrsg.)
2022. Springer-Verlag. doi:10.1007/978-3-662-63647-3

Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations
Schotthöfer, S.; Zangrando, E.; Kusch, J.; Ceruti, G.; Tudisco, F.
2022. 36th Conference on Neural Information Processing Systems, NeurIPS 2022, Neural information processing systems foundation

Compressing audio signals with interactive and cloud-based learning material - a workshop for high-school students
Wohak, K.; Frank, M.
2022. Teaching Mathematics and its Applications: An International Journal of the IMA, 41 (3), 240–255. doi:10.1093/teamat/hrab009

Preconditioners for Batched Iterative Linear Solvers on GPUs
Aggarwal, I.; Nayak, P.; Kashi, A.; Anzt, H.
2022. Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation – 22nd Smoky Mountains Computational Sciences and Engineering Conference, SMC 2022, Virtual Event, August 23–25, 2022, Revised Selected Papers. Ed.: K. Doug, 38–53, Springer Nature Switzerland. doi:10.1007/978-3-031-23606-8_3

Practical field-scale simulation approaches for quantification of fault-related leakage under uncertainty
Gasda, S.; Keilegavlen, E.; Sandve, T. H.; Berge, R.; Pettersson, P.; Krumscheid, S.
2022. Proceedings of the 16th Greenhouse Gas Control Technologies Conference. 16th International Conference on Greenhouse Gas Control Technologies (GHGT-16) 23-27 Oct 2022, 1–12. doi:10.2139/ssrn.4277020

Prediction of Optimal Solvers for Sparse Linear Systems Using Deep Learning
Funk, Y.; Götz, M.; Anzt, H.
2022. Proceedings of the 2022 SIAM Conference on Parallel Processing for Scientific Computing (PP). Ed.: X. Li, 14–24, Society for Industrial and Applied Mathematics (SIAM). doi:10.1137/1.9781611977141.2

Teaching data science in school: Digital learning material on predictive text systems
Hofmann, S.; Frank, M.
2022. Twelfth Congress of the European Society for Research in Mathematics Education (CERME12)

Erneuerbare Energien – Modellierung und Optimierung eines Solarkraftwerks
Schönbrodt, S.
2022. Neue Materialien für einen realitätsbezogenen Mathematikunterricht. Hrsg.: M. Frank, 15–69, Springer Spektrum. doi:10.1007/978-3-662-63647-3_3

Aufbau und Einsatzmöglichkeiten des Lehr- und Lernmaterials
Gerhard, M.; Hattebuhr, M.; Schönbrodt, S.; Wohak, K.
2022. Neue Materialien für einen realitätsbezogenen Mathematikunterricht. Hrsg.: M. Frank, 7–14, Springer Spektrum. doi:10.1007/978-3-662-63647-3_2

Einführung
Frank, M.; Roeckerath, C.; Schönbrodt, S.
2022. Neue Materialien für einen realitätsbezogenen Mathematikunterricht. Hrsg.: M. Frank, 1–6, Springer Spektrum. doi:10.1007/978-3-662-63647-3_1

Data Science and Machine Learning in mathematics education: Highschool students working on the Netflix Prize
Schönbrodt, S.; Frank, M.
2022. Twelfth Congress of the European Society for Research in Mathematics Education (CERME12), Feb 2022, Bozen-Bolzano, Italy

Combined effects of heat loss and curvature on turbulent flame-wall interaction in a premixed dimethyl ether/air flame
Kaddar, D.; Steinhausen, M.; Zirwes, T.; Bockhorn, H.; Hasse, C.; Ferraro, F.
2022. Proceedings of the Combustion Institute, 39 (2), 2199–2208. doi:10.1016/j.proci.2022.08.060

Memory effects of local flame dynamics in turbulent premixed flames
Zirwes, T.; Zhang, F.; Bockhorn, H.
2022. Proceedings of the Combustion Institute, 39 (2), 2349–2358. doi:10.1016/j.proci.2022.07.187

Are Altmetrics Useful for Assessing Scientific Impact? A Survey
Shakeel, Y.; Alchokr, R.; Krüger, J.; Leich, T.; Saake, G.
2022. MEDES 2022 : 14th International Conference on Management of Digital EcoSystems, Venice, Italy, 20-21 October 2022, 144–147, ACM Digital Library

Correlation of heat loss with quenching distance during transient flame-Wall interaction
Zhang, F.; Zirwes, T.; Häber, T.; Bockhorn, H.; Trimis, D.; Suntz, R.; Stapf, D.
2022. Proceedings of the Combustion Institute, 39 (2), 2037–2045. doi:10.1016/j.proci.2022.10.010

Non-destructive Material Characterization of Waste Packages with QUANTOM - 22208
Herbell, H.; Coquard, L.; Hummel, J.; Nordhardt, G.; Veltkamp, T.; Havenith, A.; Krycki, K.; Fu, B.; Helmes, C.; Doemeland, M.; Heidner, M.; Simons, F.; Köble, T.; Schumann, O.; Jesser, A.
2022

A container-based workflow for distributed training of deep learning algorithms in HPC clusters
González-Abad, J.; López García, Á.; Kozlov, V. Y.
2022. Cluster Computing, 26 (5), 2815–2834. doi:10.1007/s10586-022-03798-7

Providing performance portable numerics for Intel GPUs
Tsai, Y.-H. M.; Cojean, T.; Anzt, H.
2022. Concurrency and Computation: Practice and Experience, 35 (20), Art.-Nr.: e7400. doi:10.1002/cpe.7400

The impact of tumor metabolic activity assessed by F-FET amino acid PET imaging in particle radiotherapy of high-grade glioma patients
Waltenberger, M.; Furkel, J.; Röhrich, M.; Salome, P.; Debus, C.; Tawk, B.; Gahlawat, A. W.; Kudak, A.; Dostal, M.; Wirkner, U.; Schwager, C.; Herold-Mende, C.; Combs, S. E.; König, L.; Debus, J.; u. a.
2022. Frontiers in Oncology, 12, Art.Nr. 901390. doi:10.3389/fonc.2022.901390

A Novel Semi-supervised Clustering Algorithm: CoExDBSCAN
Ertl, B.; Schneider, M.; Meyer, J.; Streit, A.
2022. Knowledge Discovery, Knowledge Engineering and Knowledge Management – 12th International Joint Conference, IC3K 2020, Virtual Event, November 2-4, 2020, Revised Selected Papers. Ed.: A. Fred, 1–21, Springer International Publishing. doi:10.1007/978-3-031-14602-2_1

A Closer Look into Collaborative Publishing at Software-Engineering Conferences
Alchokr, R.; Krüger, J.; Shakeel, Y.; Saake, G.
2022. Linking Theory and Practice of Digital Libraries – 26th International Conference on Theory and Practice of Digital Libraries, TPDL 2022, Padua, Italy, September 20–23, 2022, Proceedings. Ed.: G. Silvello, 395–402, Springer International Publishing. doi:10.1007/978-3-031-16802-4_38

Developing the EOSC-Pillar RDM Training and Support Catalogue
Garcia, P. O.; Berberi, L.; Candela, L.; Van Nieuwerburgh, I.; Lazzeri, E.; Czuray, M.
2022. Linking Theory and Practice of Digital Libraries – 26th International Conference on Theory and Practice of Digital Libraries, TPDL 2022, Padua, Italy, September 20–23, 2022, Proceedings. Ed.: G. Silvello, 274–281, Springer International Publishing. doi:10.1007/978-3-031-16802-4_22

Weighted Altmetric Scores to Facilitate Literature Analyses
Shakeel, Y.; Bharti, A.; Leich, T.; Saake, G.
2022. Linking Theory :Practice of Digital Libraries – 26th International Conference on Theory and Practice of Digital Libraries, TPDL 2022, Padua, Italy, September 20–23, 2022, Proceedings. Ed.: G. Silvello, 459–465, Springer. doi:10.1007/978-3-031-16802-4_46

Realizing FAIR Digital Objects for the German Helmholtz Association of Research Centres
Jejkal, T.; Pfeil, A.; Schweikert, J.; Pirogov, A.; Barranco, P.; Krebs, F.; Koch, C.; Guenther, G.; Curdt, C.; Weinelt, M.
2022. Research Ideas and Outcomes, 8, Art.Nr. e94758. doi:10.3897/rio.8.e94758

Pt nanoparticles under oxidizing conditions – implications of particle size, adsorption sites and oxygen coverage on stability
Yohannes, A. G.; Fink, K.; Kondov, I.
2022. Nanoscale Advances, 4 (21), 4554–4569. doi:10.1039/D2NA00490A

Plateau proposal distributions for adaptive component-wise multiple-try metropolis
Lau, F. D.-H.; Krumscheid, S.
2022. METRON, 80, Art.Nr. 106003. doi:10.1007/s40300-022-00235-y

Adaptive stratified sampling for non-smooth problems
Pettersson, P.; Krumscheid, S.
2022. International Journal for Uncertainty Quantification, 12 (6), 71–99. doi:10.1615/Int.J.UncertaintyQuantification.2022041034

A Process Warehouse for Process Variants Analysis
Berberi, L.
2022. Big Data Analytics and Knowledge Discovery – 24th International Conference, DaWaK 2022, Vienna, Austria, August 22–24, 2022, Proceedings. Ed.: R. Wrembel, 87–93, Springer International Publishing. doi:10.1007/978-3-031-12670-3_8

Compressed basis GMRES on high-performance graphics processing units
Aliaga, J. I.; Anzt, H.; Grützmacher, T.; Quintana-Ortí, E. S.; Tomás, A. E.
2022. The International Journal of High Performance Computing Applications, 37 (2), 82–100. doi:10.1177/10943420221115140

Synergetic use of IASI profile and TROPOMI total-column level 2 methane retrieval products
Schneider, M.; Ertl, B.; Tu, Q.; Diekmann, C. J.; Khosrawi, F.; Röhling, A. N.; Hase, F.; Dubravica, D.; García, O. E.; Sepúlveda, E.; Borsdorff, T.; Landgraf, J.; Lorente, A.; Butz, A.; Chen, H.; u. a.
2022. Atmospheric Measurement Techniques, 15 (14), 4339–4371. doi:10.5194/amt-15-4339-2022

Towards a Similarity Algorithm for Controlled Vocabularies Within the Digital Humanities
Ernst, F.
2022. The Semantic Web: ESWC 2022 Satellite Events ; Hersonissos, Crete, Greece, May 29 – June 2, 2022, Proceedings. Ed.: P. Groth, 179–188, Springer International Publishing. doi:10.1007/978-3-031-11609-4_33

Quantifying CH emissions in hard coal mines from TROPOMI and IASI observations using the wind-assigned anomaly method
Tu, Q.; Schneider, M.; Hase, F.; Khosrawi, F.; Ertl, B.; Necki, J.; Dubravica, D.; Diekmann, C. J.; Blumenstock, T.; Fang, D.
2022. Atmospheric Chemistry and Physics, 22 (15), 9747–9765. doi:10.5194/acp-22-9747-2022

Dynamics of Premixed Hydrogen/Air Flames in Unsteady Flow
Zhang, F.; Zirwes, T.; Wang, Y.; Chen, Z.; Bockhorn, H.; Trimis, D.; Stapf, D.
2022. Physics of Fluids, 34 (8), Art.-Nr.: 085121. doi:10.1063/5.0098883

Porting Sparse Linear Algebra to Intel GPUs
Tsai, Y. M.; Cojean, T.; Anzt, H.
2022. Euro-Par 2021: Parallel Processing Workshops – Euro-Par 2021 International Workshops, Lisbon, Portugal, August 30-31, 2021, Revised Selected Papers. Ed.: R. Chaves, 57–68, Springer International Publishing. doi:10.1007/978-3-031-06156-1_5

Towards a Network of Sixteenth Century Book Illustrations
Götzelmann, G.
2022. T. Andrews, F. Diehr, T. Efer, A. Kuczera & J. van Zundert (Hrsg.), Graph Technologies in the Humanities : Proceedings 2020. Ed.: T. Andrews, 38–59, CEUR-WS.org

Automating and Scaling Task-Level Parallelism of Tightly Coupled Models via Code Generation
Roozmeh, M.; Kondov, I.
2022. Computational Science – ICCS 2022. Pt. 4. Ed.: D. Groen, 69–82, Springer Nature Switzerland. doi:10.1007/978-3-031-08760-8_6

Investigation of spaceborne trace gas products over St Petersburg and Yekaterinburg, Russia, by using COllaborative Column Carbon Observing Network (COCCON) observations
Alberti, C.; Tu, Q.; Hase, F.; Makarova, M. V.; Gribanov, K.; Foka, S. C.; Zakharov, V.; Blumenstock, T.; Buchwitz, M.; Diekmann, C.; Ertl, B.; Frey, M. M.; Imhasin, H. K.; Ionov, D. V.; Khosrawi, F.; u. a.
2022. Atmospheric Measurement Techniques, 15 (7), 2199–2229. doi:10.5194/amt-15-2199-2022

From a Dynamic Image Annotation Process within the Humanities to a Canonical Workflow
Pfeil, A.; Jejkal, T.; Tonne, D.; Götzelmann, G.
2022. Data Intelligence, 4 (2), 386–397. doi:10.1162/dint_a_00138

Challenge of modelling GLORIA observations of upper troposphere-lowermost stratosphere trace gas and cloud distributions at high latitudes: A case study with state-of-The-Art models
Haenel, F.; Woiwode, W.; Buchmüller, J.; Friedl-Vallon, F.; Höpfner, M.; Johansson, S.; Khosrawi, F.; Kirner, O.; Kleinert, A.; Oelhaf, H.; Orphal, J.; Ruhnke, R.; Sinnhuber, B.-M.; Ungermann, J.; Weimer, M.; u. a.
2022. Atmospheric Chemistry and Physics, 22 (4), 2843–2870. doi:10.5194/acp-22-2843-2022

Design and description of the MUSICA IASI full retrieval product
Schneider, M.; Ertl, B.; Diekmann, C. J.; Khosrawi, F.; Weber, A.; Hase, F.; Höpfner, M.; García, O. E.; Sepúlveda, E.; Kinnison, D.
2022. Earth System Science Data, 14 (2), 709–742. doi:10.5194/essd-14-709-2022

Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing
Anzt, H.; Cojean, T.; Flegar, G.; Göbel, F.; Grützmacher, T.; Nayak, P.; Ribizel, T.; Tsai, Y. M.; Quintana-Ortí, E. S.
2022. ACM Transactions on Mathematical Software, 48 (1), Art.-Nr.: 2. doi:10.1145/3480935

Digital Tools to Enable Collaborative Mathematical Modeling Online
Schönbrodt, S.; Wohak, K.; Frank, M.
2022. Modelling in Science Education and Learning, 15 (1), 151–174. doi:10.4995/msel.2022.16269

Partial Cross-Section Calculations for PGNAA Based on a Deterministic Neutron Transport Solver
Jesser, A.; Krycki, K.; Frank, M.
2022. Nuclear technology, 208 (7), 1114–1123. doi:10.1080/00295450.2021.2016018

Surprisingly Low Reactivity of Layered Manganese Oxide toward Water Oxidation in Fe/Ni-Free Electrolyte under Alkaline Conditions
Salmanion, M.; Kondov, I.; Vandichel, M.; Aleshkevych, P.; Najafpour, M. M.
2022. Inorganic chemistry, 61 (4), 2292–2306. doi:10.1021/acs.inorgchem.1c03665

The impact of sulfur hexafluoride (SF₆) sinks on age of air climatologies and trends
Loeffel, S.; Eichinger, R.; Garny, H.; Reddmann, T.; Fritsch, F.; Versick, S.; Stiller, G.; Haenel, F.
2022. Atmospheric chemistry and physics, 22 (2), 1175–1193. doi:10.5194/acp-22-1175-2022

Turbulent flame-wall interaction of premixed flames using Quadrature-based Moment Methods (QbMM) and tabulated chemistry: An a priori analysis
Steinhausen, M.; Zirwes, T.; Ferraro, F.; Popp, S.; Zhang, F.; Bockhorn, H.; Hasse, C.
2022. International Journal of Heat and Fluid Flow, 93, Art.-Nr.: 108913. doi:10.1016/j.ijheatfluidflow.2021.108913

Uncertainty quantification of offshore wind farms using Monte Carlo and sparse grid
Richter, P.; Wolters, J.; Frank, M.
2022. Energy Sources, Part B: Economics, Planning and Policy, 17 (1), Art.Nr. 2000520. doi:10.1080/15567249.2021.2000520

Workflow Engineering in Materials Design within the BATTERY 2030+ Project
Schaarschmidt, J.; Yuan, J.; Strunk, T.; Kondov, I.; Huber, S. P.; Pizzi, G.; Kahle, L.; Bölle, F. T.; Castelli, I. E.; Vegge, T.; Hanke, F.; Hickel, T.; Neugebauer, J.; Rêgo, C. R. C.; Wenzel, W.
2022. Advanced Energy Materials, 12 (17), Art.-Nr.: 2102638. doi:10.1002/aenm.202102638

An evaluation of tropical waves and wave forcing of the QBO in the QBOi models
Holt, L. A.; Lott, F.; Garcia, R. R.; Kiladis, G. N.; Cheng, Y.-M.; Anstey, J. A.; Braesicke, P.; Bushell, A. C.; Butchart, N.; Cagnazzo, C.; Chen, C.-C.; Chun, H.-Y.; Kawatani, Y.; Kerzenmacher, T.; Kim, Y.-H.; u. a.
2022. Quarterly journal of the Royal Meteorological Society, 148 (744), 1541–1567. doi:10.1002/qj.3827

Multidimensional Clustering for Spatio-Temporal Data and its Application in Climate Research. Dissertation
Ertl, B.
2021, Dezember 23. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000141504

Statistical model building: Background “knowledge” based on inappropriate preselection causes misspecification
Hafermann, L.; Becher, H.; Herrmann, C.; Klein, N.; Heinze, G.; Rauch, G.
2021. BMC Medical Research Methodology, 21 (1), 196. doi:10.1186/s12874-021-01373-z

CoCoNet—boosting RNA contact prediction by convolutional neural networks
Zerihun, M. B.; Pucci, F.; Schug, A.
2021. Nucleic acids research, 49 (22), 12661–12672. doi:10.1093/nar/gkab1144

HEPiX Benchmarking Solution for WLCG Computing Resources
Giordano, D.; Alef, M.; Atzori, L.; Barbet, J.-M.; Datskova, O.; Girone, M.; Hollowell, C.; Javurkova, M.; Maganza, R.; Medeiros, M. F.; Michelotto, M.; Rinaldi, L.; Sciabà, A.; Sobie, R. J.; Southwick, D.; u. a.
2021. Computing and software for big science, 5 (1), 28. doi:10.1007/s41781-021-00074-y

OPTIMADE, an API for exchanging materials data
Andersen, C. W.; Armiento, R.; Blokhin, E.; Conduit, G. J.; Dwaraknath, S.; Evans, M. L.; Fekete, Á.; Gopakumar, A.; Gražulis, S.; Merkys, A.; Mohamed, F.; Oses, C.; Pizzi, G.; Rignanese, G.-M.; Scheidgen, M.; u. a.
2021. Scientific data, 8 (1), Art.-Nr.: 217. doi:10.1038/s41597-021-00974-z

bamlss : A Lego Toolbox for Flexible Bayesian Regression (and Beyond)
Umlauf, N.; Klein, N.; Simon, T.; Zeileis, A.
2021. Journal of Statistical Software, 100 (4). doi:10.18637/jss.v100.i04

Memory Effects in Premixed Flames: Unraveling Transient Flame Dynamics with the Flame Particle Tracking Method. Dissertation
Zirwes, T. T.
2021, Oktober 29. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000139504

A Lagrangian perspective on stable water isotopes during the West African Monsoon
Diekmann, C. J.; Schneider, M.; Knippertz, P.; Vries, A. J.; Pfahl, S.; Aemisegger, F.; Dahinden, F.; Ertl, B.; Khosrawi, F.; Wernli, H.; Braesicke, P.
2021. Journal of geophysical research / D, 126 (19), e2021JD034895. doi:10.1029/2021JD034895

Collection of Job Scheduling Prediction Methods
Soysal, M.; Streit, A.
2021. Job Scheduling Strategies for Parallel Processing: 24th International Workshop, JSSPP 2021, Virtual Event, May 21, 2021, Revised Selected Papers. Ed.: D. Klusáček, 35–42, Springer-Verlag. doi:10.1007/978-3-030-88224-2_2

Assessment and Adjustment of Approximate Inference Algorithms Using the Law of Total Variance
Yu, X.; Nott, D. J.; Tran, M.-N.; Klein, N.
2021. Journal of Computational and Graphical Statistics, 30 (4), 977–990. doi:10.1080/10618600.2021.1880921

Interactive Labeling for Human Pose Estimation in Surveillance Videos
Cormier, M.; Ropke, F.; Golda, T.; Beyerer, J.
2021. 2021 IEEE/CVF International Conference on Computer Vision Workshops : ICCVW 2021 : 11-17 October 2021, virtual event : proceedings. Ed.: Tamara Berg, 1649–1658, IEEEXplore. doi:10.1109/ICCVW54120.2021.00190

Analysis of Process Variants with a Process Warehouse Approach. Dissertation
Berberi, L.
2021, September 30

Simulations of Air-assisted Primary Atomization at Different Air-to-Liquid Injection Angles for Entrained Flow Gasification
Zhang, F.; Zirwes, T.; Wachter, S.; Jakobs, T.; Habisreuther, P.; Zarzalis, N.; Trimis, D.; Kolb, T.; Bockhorn, H.
2021. 30. Deutscher Flammentag, Deutsche Sektion des Combustion Institutes und DVV/VDI-Gesellschaft Energie und Umwelt. Ed.: F. Dinkelacker, 1116–1125

Bayesian variable selection for non‐Gaussian responses: a marginally calibrated copula approach
Klein, N.; Smith, M. S.
2021. Biometrics, 77 (3), 809–823. doi:10.1111/biom.13355

Didaktisch-methodische Entwicklung und Evaluation von computergestützten Lehr- und Lernmaterialien zur Mathematik inverser Probleme. Dissertation
Wohak, K.
2021, August 24. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000136535

Deriving Protein Structures Efficiently by Integrating Experimental Data into Biomolecular Simulations. Dissertation
Weiel-Potyagaylo, M.
2021, August 11. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000136249

A structure-preserving surrogate model for the closure of the moment system of the Boltzmann equation using convex deep neural networks
Schotthöfer, S.; Xiao, T.; Frank, M.; Hauck, C.
2021. AIAA Aviation 2021 Forum: August 2-6, 2021 ; Virtual Event, American Institute of Aeronautics and Astronautics. doi:10.2514/6.2021-2895

Correction to: Quasi-DNS Dataset of a Piloted Flame with Inhomogeneous Inlet Conditions
Zirwes, T.; Zhang, F.; Habisreuther, P.; Hansinger, M.; Bockhorn, H.; Pfitzner, M.; Trimis, D.
2021. Flow, turbulence and combustion, 107 (2), 517. doi:10.1007/s10494-021-00244-3

Heat Release Rate Markers for Highly Stretched Premixed CH/Air and CH/H/Air Flames
Chen, X.; Wang, Y.; Zirwes, T.; Zhang, F.; Bockhorn, H.; Chen, Z.
2021. Energy & fuels, 35 (16), 13349–13359. doi:10.1021/acs.energyfuels.1c02187

Dynamic particle swarm optimization of biomolecular simulation parameters with flexible objective functions
Weiel, M.; Götz, M.; Klein, A.; Coquelin, D.; Floca, R.; Schug, A.
2021. Nature machine intelligence, 3 (8), 727–734. doi:10.1038/s42256-021-00366-3

Transparent Integration of Opportunistic Resources into the WLCG Compute Infrastructure
Böhler, M.; Caspart, R.; Fischer, M.; Freyermuth, O.; Giffels, M.; Kroboth, S.; Kuehn, E.; Schnepf, M.; Cube, F. von; Wienemann, P.
2021. The European physical journal / Web of Conferences, 251, Art.-Nr.: 02039. doi:10.1051/epjconf/202125102039

Interoperabilität von Metadaten innerhalb der NFDI: Konsortienübergreifender Metadaten-Workshop am 2./3. Juli 2020
Iglezakis, D.; Fuhrmans, M.; Arndt, S.; Demandt, É.; Hachinger, S.; Hausen, D.; Lanza, G.; Lipp, J.; Stotzka, R.; Terzijska, D.
2021. Bausteine Forschungsdatenmanagement, (2), 124–135. doi:10.17192/bfdm.2021.2.8313

Bayesian Inference for Regression Copulas
Smith, M. S.; Klein, N.
2021. Journal of Business & Economic Statistics, 39 (3), 712–728. doi:10.1080/07350015.2020.1721295

Complexity Analysis of stochastic gradient methods for PDE-constrained optimal Control Problems with uncertain parameters
Martin, M.; Krumscheid, S.; Nobile, F.
2021. ESAIM: Mathematical Modelling and Numerical Analysis, 55 (4), 1599–1633. doi:10.1051/m2an/2021025

Evolutionary Optimization of Neural Architectures in Remote Sensing Classification Problems
Coquelin, D.; Sedona, R.; Riedel, M.; Götz, M.
2021. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 12-16 July 2021, 1587–1590, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS47720.2021.9554309

Mountain-wave-induced polar stratospheric clouds and their representation in the global chemistry model ICON-ART
Weimer, M.; Buchmüller, J.; Hoffmann, L.; Kirner, O.; Luo, B.; Ruhnke, R.; Steiner, M.; Tritscher, I.; Braesicke, P.
2021. Atmospheric chemistry and physics, 21 (12), 9515–9543. doi:10.5194/acp-21-9515-2021

Semi-Supervised Time Point Clustering for Multivariate Time Series
Ertl, B.; Meyer, J.; Schneider, M.; Streit, A.
2021. Proceedings of the 34th Canadian Conference on Artificial Intelligence. Ed.: L. Antonie, Article: 2021L05, Canadian Artificial Intelligence Association. doi:10.21428/594757db.9fa1eff5

Bayesian Effect Selection in Structured Additive Distributional Regression Models
Klein, N.; Carlan, M.; Kneib, T.; Lang, S.; Wagner, H.
2021. Bayesian Analysis, 16 (2), 545–573. doi:10.1214/20-BA1214

High-Throughput screening of the CoRE MOF database to predict cross-linking of Metal-Organic Frameworks. Dissertation
Ahmad, M.
2021, Mai 12. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000132463

A stochastic kinetic scheme for multi-scale plasma transport with uncertainty quantification
Xiao, T.; Frank, M.
2021. Journal of computational physics, 432, Art.-Nr. 110139. doi:10.1016/j.jcp.2021.110139

Evaluating asynchronous Schwarz solvers on GPUs
Nayak, P.; Cojean, T.; Anzt, H.
2021. The international journal of high performance computing applications, 35 (3), 226–236. doi:10.1177/1094342020946814

Thermal Analysis of a Solar External Receiver Tube with a Novel Component of Guide Vanes
Tu, Z.; Piccioni Koch, D.; Sarunac, N.; Frank, M.; Mao, J.
2021. Energies, 14 (8), Article no: 2253. doi:10.3390/en14082253

Marginally Calibrated Deep Distributional Regression
Klein, N.; Nott, D. J.; Smith, M. S.
2021. Journal of Computational and Graphical Statistics, 30 (2), 467–483. doi:10.1080/10618600.2020.1807996

The Trimeric Major Capsid Protein of Mavirus is stabilized by its Interlocked N-termini Enabling Core Flexibility for Capsid Assembly
Christiansen, A.; Weiel, M.; Winkler, A.; Schug, A.; Reinstein, J.
2021. Journal of Molecular Biology, 433 (7), Art.-Nr.: 166859. doi:10.1016/j.jmb.2021.166859

Adaptive Precision Block-Jacobi for High Performance Preconditioning in the Ginkgo Linear Algebra Software
Flegar, G.; Anzt, H.; Cojean, T.; Quintana-Ortí, E. S.
2021. ACM transactions on mathematical software, 47 (2), 1–28. doi:10.1145/3441850

An Eulerian-Lagrangian method for wet biomass carbonization in rotary kiln reactors
Tavakkol, S.; Zirwes, T.; Denev, J. A.; Jamshidi, F.; Weber, N.; Bockhorn, H.; Trimis, D.
2021. Renewable & sustainable energy reviews, 139, Art.-Nr.: 110582. doi:10.1016/j.rser.2020.110582

Exploring Scheduling for On-demand File Systems and Data Management within HPC Environments. Dissertation
Soysal, M.
2021, März 17. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000130537/v2

Potential of Mid-tropospheric Water Vapor Isotopes to Improve Large-Scale Circulation and Weather Predictability
Toride, K.; Yoshimura, K.; Tada, M.; Diekmann, C.; Ertl, B.; Khosrawi, F.; Schneider, M.
2021. Geophysical Research Letters, 48 (5), Art.Nr.e2020GL091698. doi:10.1029/2020GL091698

Theory, models, and numerical methods for classical and non-classical transport. Dissertation
Camminady, T.
2021, Februar 1. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000128846

Cardiorespiratory, Metabolic and Perceived Responses to Electrical Stimulation of Upper‐Body Muscles While Performing Arm Cycling
Zinner, C.; Matzka, M.; Krumscheid, S.; Holmberg, H.-C.; Sperlich, B.
2021. Journal of Human Kinetics, 77 (1), 117–123. doi:10.2478/hukin-2021-0016

EOSC Authentication and Authorization Infrastructure (AAI) : Report from the EOSC Executive Board Working Group (WG) Architecture AAI Task Force (TF)
Wierenga, K.; Johansson, L.; Kanellopoulos, C.; Groep, D.; Vaghetti, D.; Liampotis, N.; Sanden, M. van de; Reetz, J.; Alam, S.; Linden, M.; Jensen, J.; Dijk, N. van; Ceccanti, A.; Apweiler, S.; Abt, B.; u. a.
2021. European Commission (EU). doi:10.2777/8702

In search of lost edges: a case study on reconstructing financial networks
Lebacher, M.; Klein, N.; Kauermann, G.; Cook, S.
2021. The Journal of Network Theory in Finance, 29–61. doi:10.21314/JNTF.2019.058

The GridKa tape storage: latest improvements and current production setup
Musheghyan, H.; Ambroj Pérez, S.; Petzold, A.; Ressmann, D.; Sundermann, J. E.
2021. EPJ Web of Conferences, 251, Art.-Nr.: 02014. doi:10.1051/epjconf/202125102014

Batched Sparse Iterative Solvers for Computational Chemistry Simulations on GPUs
Aggarwal, I.; Kashi, A.; Nayak, P.; Balos, C. J.; Woodward, C. S.; Anzt, H.
2021. Proceedings of ScalA 2021: 12th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems: Held in conjunction with SC21: The International Conference for High Performance Computing, Networking, Storage and Analysis ; St. Louis, Missouri, USA, November 14-19, 2021, 35–43, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ScalA54577.2021.00010

Numerical Solution Strategies in Permeation Processes
Weth, A. von der; Koch, D. P.; Arbeiter, F.; Glage, T.; Klimenko, D.; Schlindwein, G.; Pasler, V.; Prothmann, N.; Zinn, K.
2021. Defect and diffusion forum, 413, 29–46. doi:10.4028/www.scientific.net/DDF.413.29

Implementation and Validation of a Computationally Efficient DNS Solver for Reacting Flows in OpenFOAM
Zirwes, T.; Zhang, F.; Habisreuther, P.; Denev, J.; Bockhorn, H.; Trimis, D.
2021. 14th WCCM-ECCOMAS Congress 2020: Collection of papers presented at the 14th edition of the WCCM-ECCOMAS, virtual congress, January, 11-15, 2021. Ed.: F. Chinesta, Scipedia S.L. doi:10.23967/wccm-eccomas.2020.175

DNS of Near Wall Dynamics of Premixed CH/Air Flames
Zhang, F.; Zirwes, T.; Häber, T.; Bockhorn, H.; Trimis, D.; Suntz, R.
2021. 14th WCCM-ECCOMAS Congress 2020: Collection of papers presented at the 14th edition of the WCCM-ECCOMAS, virtual congress, January, 11-15, 2021. Ed.: F. Chinesta, Scipedia S.L. doi:10.23967/wccm-eccomas.2020.123

Hybrid eulerian-lagrangian approach for dense spray simulations
Heidarifatasmi, H.; Zirwes, T.; Zhang, F.; Habisreuther, P.; Trimis, D.
2021. Graph Drawing and Network Visualization: 29th International Symposium, GD 2021, Tübingen, Germany, September 14–17, 2021, Revised Selected Papers. Ed.: H. C. Purchase, 1–12, Scipedia S.L. doi:10.23967/wccm-eccomas.2020.172

On the analytical inversion of solver matrices used in numerical approximations for the diffusion equation
Glage, T.; Weth, A. von der; Arbeiter, F.; Koch, D. P.
2021. Defect and Diffusion Forum, 413, 3–18. doi:10.4028/www.scientific.net/DDF.413.3

Metadata schema to support FAIR data in scanning electron microscopy
Joseph, R.; Chauhan, A.; Eschke, C.; Ihsan, A. Z.; Jalali, M.; Jäntsch, U.; Jung, N.; Shyam Kumar, C. N.; Kübel, C.; Lucas, C.; Mail, M.; Mazilkin, A.; Neidiger, C.; Panighel, M.; Sandfeld, S.; u. a.
2021. Supplementary Proceedings of the XXIII International Conference on Data Analytics and Management in Data Intensive Domains (DAMDID/RCDL 2021): Moscow, Russia, October 26-29, 2021. Ed.: A. Pozanenko, 265–277, CEUR-WS.org

Enhancing OpenFOAM’s Performance on HPC Systems
Zirwes, T.; Zhang, F.; Denev, J. A.; Habisreuther, P.; Bockhorn, H.; Trimis, D.
2021. High Performance Computing in Science and Engineering ’19 – Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2019. Ed.: W. Nagel, 225–239, Springer International Publishing. doi:10.1007/978-3-030-66792-4_16

Ad-Hoc File Systems At Extreme Scales
Soysal, M.; Streit, A.
2021. High Performance Computing in Science and Engineering ’19 – Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2019. Ed.: W. Nagel, 537–549, Springer International Publishing. doi:10.1007/978-3-030-66792-4_36

The Michelson Interferometer for Passive Atmospheric Sounding global climatology of BrONO2 2002–2012: a test for stratospheric bromine chemistry
Höpfner, M.; Kirner, O.; Wetzel, G.; Sinnhuber, B.-M.; Haenel, F.; Johansson, S.; Orphal, J.; Ruhnke, R.; Stiller, G.; Clarmann, T. von
2021. Atmospheric chemistry and physics, 21 (24), 18433–18464. doi:10.5194/acp-21-18433-2021

Chemotion Repository, a Curated Repository for Reaction Information and Analytical Data
Tremouilhac, P.; Huang, P.-C.; Lin, C.-L.; Huang, Y.-C.; Nguyen, A.; Jung, N.; Bach, F.; Bräse, S.
2021. Chemistry methods, 1 (1), 8–11. doi:10.1002/cmtd.202000034

NFDI4Chem – Infrastruktur für den digitalen Wandel in der Chemischen Forschung
Jung, N.; Neumann, S.; Koepler, O.; Bach, F.; Popp, C.; Herres-Pawlis, S.; Liermann, J.; Razum, M.; Steinbeck, C.
2021. Bunsen-Magazin, 23 (2), 100–103. doi:10.26125/r978-6f93

MoMaF Science Data Center für Molekulare Materialforschung
Altschuh, P.; Bach, F.; Bräse, S.; Hartmann, T.; Jung, N.; Krauß, P.; Nestler, B.; Schiefer, G.; Schreiber, C.; Selzer, M.; Terzijska, D.
2021. E-Science-Tage 2021: Share Your Research Data, Heidelberg, 04.03. - 05.03.2021. doi:10.11588/heidok.00029699

Authentische und relevante Modellierung mit Schülerinnen und Schülern an nur einem Tag?!
Wohak, K.; Sube, M.; Schönbrodt, S.; Roeckerath, C.; Frank, M.
2021. Neue Materialien für einen realitätsbezogenen Mathematikunterricht 8 – ISTRON-Schriftenreihe. Ed.: M. Bracke, 37–50, Springer Fachmedien Wiesbaden. doi:10.1007/978-3-658-33012-5_4

Digitales Lernmaterial zur Netflix Challenge
Schönbrodt, S.; Frank, M.
2021. Beiträge zum Mathematikunterricht 2021. Hrsg.: Kerstin Hein, Cathleen Heil, Silke Ruwisch & Susanne Prediger, WTM Verlag für wissenschaftliche Texte und Medien. doi:10.17877/DE290R-22328

Zerstörungsfreie stoffliche Beschreibung und Plausibilitätsprüfung radioaktiver Abfälle mittels QUANTOM
Coquard, L.; Nordhardt, G.; Hummel, J.; Havenith, A.; Krycki, K.; Hirsch, M.; Wangnick, M.; Fu, B.; Reisenhofer, F.; Hansmann, B.; Hansmann, T.; Helmes, C.; Dürr, M.; Rother, M.; Simons, F.; u. a.
2021. KONTEC GmbH

The global and multi-annual MUSICA IASI {H2O, δD} pair dataset
Diekmann, C. J.; Schneider, M.; Ertl, B.; Hase, F.; García, O.; Khosrawi, F.; Sepúlveda, E.; Knippertz, P.; Braesicke, P.
2021. Earth system science data, 13 (11), 5273–5292. doi:10.5194/essd-13-5273-2021

Sektionskonzept Meta(daten), Terminologien und Provenienz zur Einrichtung einer Sektion im Verein Nationale Forschungsdateninfrastruktur (NFDI) e.V
Koepler, O.; Schrade, T.; Neumann, S.; Stotzka, R.; Wiljes, C.; Blümel, I.; Bracht, C.; Hamann, T.; Arndt, S.; Hunold, J.
2021. Zenodo. doi:10.5281/zenodo.5619089

Numerical database of highly-resolved turbulent flame-wall interaction simulations for model validation
Zirwes, T.; Zhang, F.; Steinhausen, M.; Habisreuther, P.; Bockhorn, H.; Hasse, C.; Trimis, D.
2021. 30. Deutscher Flammentag, Deutsche Sektion des Combustion Institutes und DVV/VDI-Gesellschaft Energie und Umwelt. Ed.: Dinkelacker, Friedrich; Pitsch Heinz; Scherer, Viktor, 1144–1153

DNS of Unsteady Flame-Wall Interaction
Zhang, F.; Zirwes, T.; Häber, T.; Bockhorn, H.; Trimis, D.; Wang, R.; Suntz, R.
2021. 30. Deutscher Flammentag, Deutsche Sektion des Combustion Institutes und DVV/VDI-Gesellschaft Energie und Umwelt. Ed.: F. Dinkelacker, H. Pitsch, V. Scherer, 1106–1115

Efficient uncertainty quantification for Monte Carlo dose calculations using importance (re-)weighting
Stammer, P.; Burigo, L.; J kel, O.; Frank, M.; Wahl, N.
2021. Physics in Medicine and Biology, 66 (20), 205003. doi:10.1088/1361-6560/ac287f

Mathematische Grundlagen der Künstlichen Intelligenz im Schulunterricht: Chancen für eine Bereicherung des Unterrichts in linearer Algebra
Schönbrodt, S.; Camminady, T.; Frank, M.
2021. Mathematische Semesterberichte, 69, 73–101. doi:10.1007/s00591-021-00310-x

Mixed Precision Incomplete and Factorized Sparse Approximate Inverse Preconditioning on GPUs
Göbel, F.; Grützmacher, T.; Ribizel, T.; Anzt, H.
2021. Euro-Par 2021: Parallel Processing: 27th International Conference on Parallel and Distributed Computing, Lisbon, Portugal, September 1–3, 2021, Proceedings. Ed.: L. Sousa, 550–564, Springer-Verlag. doi:10.1007/978-3-030-85665-6_34

Retrieval of Water Vapour Profiles from GLORIA Nadir Observations
König, N.; Wetzel, G.; Höpfner, M.; Friedl-Vallon, F.; Johansson, S.; Kleinert, A.; Schneider, M.; Ertl, B.; Ungermann, J.
2021. Remote sensing, 13 (18), Article no: 3675. doi:10.3390/rs13183675

Odderon Exchange from Elastic Scattering Differences between pp and pp Data at 1.96 TeV and from pp Forward Scattering Measurements
Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Alves, G. A.; Antchev, G.; Askew, A.; Aspell, P.; Assis Jesus, A. C. S.; Atanassov, I.; u. a.
2021. Physical Review Letters, 127 (6), Art.-Nr.: 062003. doi:10.1103/PhysRevLett.127.062003

Digitale Erforschung epistemischer Verflechtungen : Informationsinfrastruktur und vormoderne Wissenstransfers
Krewet, M.; Kahl, J.; Götzelmann, G.; Hübner, J.; Hegel, P.; Söring, S.; Tonne, D.
2021. Wissensoikonomien. Hrsg.: N. Schmidt, 135–150, Harrassowitz Verlag

A Collaborative Peer Review Process for Grading Coding Assignments
Nayak, P.; Göbel, F.; Anzt, H.
2021. Computational Science – ICCS 2021: 21st International Conference, Krakow, Poland, June 16–18, 2021, Proceedings, Part VI. Ed.: M. Paszynski, 654–660, Springer-Verlag. doi:10.1007/978-3-030-77980-1_49

Search for the decay B →η’η
Belle Collaboration; Nisar, N. K.; Savinov, V.; Adachi, I.; Aihara, H.; Al Said, S.; Asner, D. M.; Atmacan, H.; Aushev, T.; Ayad, R.; Babu, V.; Bahinipati, S.; Behera, P.; Bennett, J.; Bessner, M.; u. a.
2021. Physical review / D, 104 (3), Art.-Nr.: L031101. doi:10.1103/PhysRevD.104.L031101

AI-based thermal bridge detection of building rooftops on district scale using aerial images
Mayer, Z.; Kahn, J.; Hou, Y.; Volk, R.
2021. EG-ICE 2021 Workshop on Intelligent Computing in Engineering. Ed.: Jimmy Abualdenien, André Borrmann, Lucian-Constantin Ungureanu, Timo Hartmann, 497–507, Universitätsverlag der TU Berlin

Erratum: Measurement of the CKM matrix element |V| from B → D lv at Belle [Phys. Rev. / D, vol. 100, Art.Nr. 052007, 2019; DOI: 10.1103/PhysRevD.100.052007 ]
Belle Collaboration; Waheed, E.; Urquijo, P.; Ferlewicz, D.; Adachi, I.; Adamczyk, K.; Aihara, H.; Al Said, S.; Asner, D. M.; Atmacan, H.; Aushev, T.; Ayad, R.; Babu, V.; Badhrees, I.; Bansal, V.; u. a.
2021. Physical review / D, 103 (7), Art.Nr.: 079901. doi:10.1103/PhysRevD.103.079901

Measurement of branching fractions and CP asymmetries for D →K(η,π) and D → π(η,π) decays at Belle
Belle Collaboration; Guan, Y.; Schwartz, A. J.; Kinoshita, K.; Adachi, I.; Aihara, H.; Al Said, S.; Asner, D. M.; Atmacan, H.; Aulchenko, V.; Aushev, T.; Ayad, R.; Babu, V.; Behera, P.; Bennett, J.; u. a.
2021. Physical review / D, 103 (11), Article: 112005. doi:10.1103/PhysRevD.103.112005

Probabilistic Representation of Objects and Their Support Relations
Paus, F.; Asfour, T.
2021. Experimental Robotics : The 17th International Symposium on Experimental Robotics, November 9–12, 2020 [postponed to Nov. 15–18, 2021], Floriana, Malta. Ed.: B. Siciliano, 510–519, Springer International Publishing. doi:10.1007/978-3-030-71151-1_45

Entropy–Based Methods for Uncertainty Quantification of Hyperbolic Conservation Laws
Frank, M.; Kusch, J.; Wolters, J.
2021. Recent Advances in Numerical Methods for Hyperbolic PDE Systems – NumHyp 2019. Ed.: M. Muñoz-Ruiz, 29–56, Springer International Publishing. doi:10.1007/978-3-030-72850-2_2

An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action
Anzt, H.; Bach, F.; Druskat, S.; Löffler, F.; Loewe, A.; Renard, B. Y.; Seemann, G.; Struck, A.; Achhammer, E.; Aggarwal, P.; Appel, F.; Bader, M.; Brusch, L.; Busse, C.; Chourdakis, G.; u. a.
2021. F1000Research, 9, 295. doi:10.12688/f1000research.23224.2

A Semi-supervised Approach for Trajectory Segmentation to Identify Different Moisture Processes in the Atmosphere
Ertl, B.; Schneider, M.; Diekmann, C.; Meyer, J.; Streit, A.
2021. Computational Science – ICCS 2021 – 21st International Conference, Krakow, Poland, June 16–18, 2021, Proceedings, Part I. Ed.: M. Paszynski, 264–277, Springer International Publishing. doi:10.1007/978-3-030-77961-0_23

Evidence for X(3872)→J/ψπ+π− Produced in Single-Tag Two-Photon Interactions
Belle Collaboration; Teramoto, Y.; Uehara, S.; Masuda, M.; Adachi, I.; Aihara, H.; Al Said, S.; Asner, D. M.; Atmacan, H.; Aushev, T.; Ayad, R.; Babu, V.; Behera, P.; Beleño, C.; Bennett, J.; u. a.
2021. Physical review letters, 126 (12), Art.-Nr.: 122001. doi:10.1103/PhysRevLett.126.122001

On GPU optimizations of stencil codes for highly parallel simulations
Pfisterer, N.; Berghoff, M.; Streit, A.
2021. Proceedings 29th Euromicro International Conference on Parallel, Distributed and Network-Based Processing PDP 2021: Valladolid, Spain ; 10-12 March 2021, 228–235, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PDP52278.2021.00043

Test of Lepton-Flavor Universality in B → K*l⁺l⁻ Decays at Belle
Belle Collaboration; Wehle, S.; Adachi, I.; Adamczyk, K.; Aihara, H.; Asner, D. M.; Atmacan, H.; Aulchenko, V.; Aushev, T.; Ayad, R.; Babu, V.; Behera, P.; Berger, M.; Bhardwaj, V.; Biswal, J.; u. a.
2021. Physical review letters, 126 (16), Article: 161801. doi:10.1103/PhysRevLett.126.161801

Pollution trace gases C₂H₆, C₂H₂, HCOOH, and PAN in the North Atlantic UTLS: observations and simulations
Wetzel, G.; Friedl-Vallon, F.; Glatthor, N.; Grooß, J.-U.; Gulde, T.; Höpfner, M.; Johansson, S.; Khosrawi, F.; Kirner, O.; Kleinert, A.; Kretschmer, E.; Maucher, G.; Nordmeyer, H.; Oelhaf, H.; Orphal, J.; u. a.
2021. Atmospheric chemistry and physics, 21 (10), 8213–8232. doi:10.5194/acp-21-8213-2021

Oxygen-Evolution Reaction by a Palladium Foil in the Presence of Iron
Akbari, N.; Kondov, I.; Vandichel, M.; Aleshkevych, P.; Najafpour, M. M.
2021. Inorganic Chemistry, 60 (8), 5682–5693. doi:10.1021/acs.inorgchem.0c03746

Application of reaction-diffusion manifolds (REDIM) for the simulation of two-dimensional axisymmetric laminar diffusion flames
Li, N.; Yu, C.; Zirwes, T.; Maas, U.
2021. 10th European Combustion Meeting (ECM 2021), April 14-15, 2021, Virtual Edition. Proceedings Volume, MCM

The MUSICA IASI {HO, δD} pair product
Diekmann, C. J.; Schneider, M.; Ertl, B.; Hase, F.; García, O.; Khosrawi, F.; Sepúlveda, E.; Knippertz, P.; Braesicke, P.
2021. Earth system science data discussions. doi:10.5194/essd-2021-87

Test of lepton flavor universality and search for lepton flavor violation in B → Kℓℓ decays
Belle Collaboration; Choudhury, S.; Sandilya, S.; Trabelsi, K.; Giri, A.; Aihara, H.; Al Said, S.; Asner, D. M.; Atmacan, H.; Aulchenko, V.; Aushev, T.; Ayad, R.; Babu, V.; Bahinipati, S.; Behera, P.; u. a.
2021. Journal of high energy physics, 2021 (3), Art. Nr.: 105. doi:10.1007/JHEP03(2021)105

Balanced and Compressed Coordinate Layout for the Sparse Matrix-Vector Product on GPUs
Aliaga, J. I.; Anzt, H.; Quintana-Ortí, E. S.; Tomás, A. E.; Tsai, Y. M.
2021. Euro-Par 2020: Parallel Processing Workshops: Euro-Par 2020 International Workshops, Warsaw, Poland, August 24–25, 2020, Revised Selected Papers. Ed.: B. Balis, 83–95, Springer-Verlag. doi:10.1007/978-3-030-71593-9_7

Preparing Ginkgo for AMD GPUs – A Testimonial on Porting CUDA Code to HIP
Tsai, Y. M.; Cojean, T.; Ribizel, T.; Anzt, H.
2021. Euro-Par 2020: Parallel Processing Workshops: Euro-Par 2020 International Workshops, Warsaw, Poland, August 24–25, 2020, Revised Selected Papers. Ed.: B. Balis, 109–121, Springer-Verlag. doi:10.1007/978-3-030-71593-9_9

Intercomparison of arctic XHO observations from three ground-based Fourier transform infrared networks and application for satellite validation
Tu, Q.; Hase, F.; Blumenstock, T.; Schneider, M.; Schneider, A.; Kivi, R.; Heikkinen, P.; Ertl, B.; Diekmann, C.; Khosrawi, F.; Sommer, M.; Borsdorff, T.; Raffalski, U.
2021. Atmospheric Measurement Techniques, 14 (3), 1993–2011. doi:10.5194/amt-14-1993-2021

Predictive storage strategy for optimal design of hybrid CSP-PV plants with immersion heater
Richter, P.; Trimborn, T.; Aldenhoff, L.
2021. Solar Energy, 218, 237–250. doi:10.1016/j.solener.2020.11.005

Study of the normalized transverse momentum distribution of W bosons produced in p collisions at =1.96  TeV
Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Aushev, V.; Aushev, Y.; Avila, C.; u. a.
2021. Physical review / D, 103 (1), Art. Nr.: 012003. doi:10.1103/PhysRevD.103.012003

Technical note: “Bit by bit”: a practical and general approach for evaluating model computational complexity vs. model performance
Azmi, E.; Ehret, U.; Weijs, S. V.; Ruddell, B. L.; Perdigão, R. A. P.
2021. Hydrology and earth system sciences, 25 (2), 1103–1115. doi:10.5194/hess-25-1103-2021

Crediting pull requests to open source research software as an academic contribution
Anzt, H.; Kuehn, E.; Flegar, G.
2021. Journal of computational science, 49, Art.-Nr.: 101278. doi:10.1016/j.jocs.2020.101278

Deutschland in der European Open Science Cloud
Streit, A.; Wezel, J. van
2021. Praxishandbuch Forschungsdatenmanagement. Hrsg.: Markus Putnings, 31–52, De Gruyter Saur. doi:10.1515/9783110657807-003

Accurate interpolation methods for the annual simulation of solar central receiver systems using celestial coordinate system
Richter, P.; Tinnes, J.; Aldenhoff, L.
2021. Solar energy, 213, 328–338. doi:10.1016/j.solener.2020.10.087

Identification of Flame Regimes in Partially Premixed Combustion from a Quasi-DNS Dataset
Zirwes, T.; Zhang, F.; Habisreuther, P.; Hansinger, M.; Bockhorn, H.; Pfitzner, M.; Trimis, D.
2021. Flow, turbulence and combustion, 106 (2), 373–404. doi:10.1007/s10494-020-00228-9

In-situ flame particle tracking based on barycentric coordinates for studying local flame dynamics in pulsating Bunsen flames
Zirwes, T.; Zhang, F.; Wang, Y.; Habisreuther, P.; Denev, J. A.; Chen, Z.; Bockhorn, H.; Trimis, D.
2021. Proceedings of the Combustion Institute, 38 (2), 2057–2066. doi:10.1016/j.proci.2020.07.033

Ignition of dimethyl ether/air mixtures by hot particles: Impact of low temperature chemical reactions
Wang, Y.; Zhang, H.; Zirwes, T.; Zhang, F.; Bockhorn, H.; Chen, Z.
2021. Proceedings of the Combustion Institute, 38 (2), 2459–2466. doi:10.1016/j.proci.2020.06.254

Numerical Study of Quenching Distances for Side-Wall Quenching Using Detailed Diffusion and Chemistry
Zirwes, T.; Häber, T.; Zhang, F.; Kosaka, H.; Dreizler, A.; Steinhausen, M.; Hasse, C.; Stagni, A.; Trimis, D.; Suntz, R.; Bockhorn, H.
2021. Flow, turbulence and combustion, 106, 649–679. doi:10.1007/s10494-020-00215-0

Near Wall Dynamics of Premixed Flames
Zhang, F.; Zirwes, T.; Häber, T.; Bockhorn, H.; Trimis, D.; Suntz, R.
2021. Proceedings of the Combustion Institute, 38 (2), 1955–1964. doi:10.1016/j.proci.2020.06.058

Numerical Investigation of Local Heat-Release Rates and Thermo-Chemical States in Side-Wall Quenching of Laminar Methane and Dimethyl Ether Flames
Steinhausen, M.; Luo, Y.; Popp, S.; Straßacker, C.; Zirwes, T.; Kosaka, H.; Zentgraf, F.; Maas, U.; Sadiki, A.; Dreizler, A.; Hasse, C.
2021. Flow, turbulence and combustion, 106, 681–700. doi:10.1007/s10494-020-00146-w

Numerical Computation of Turbulent Flow Fields in a Fan-stirred Combustion Bomb
Zhang, F.; Zirwes, T.; Habisreuther, P.; Zarzalis, N.; Bockhorn, H.; Trimis, D.
2021. Combustion science and technology, 193 (4), 594–610. doi:10.1080/00102202.2019.1665520

A Guide for Publishing, Using, and Licensing Research Software in Germany
Struck, A.; Loewe, A.; Achhammer, E.; Rack, F.; Bach, F.; Löffler, F.; Seemann, G.; Anzt, H.; Funk, M.; Unger, S.; Druskat, S.; Friedl, S.
2020. Zenodo. doi:10.5281/zenodo.4327148

JAWS – Just Another Workspace Suite Data Orchestration for HPC Environments
Soysal, M.
2020. The 18th Annual Meeting of the 2020 International Conference on High Performance Computing & Simulation

The Repository Chemotion: Infrastructure for Sustainable Research in Chemistry
Tremouilhac, P.; Lin, C.-L.; Huang, P.-C.; Huang, Y.-C.; Nguyen, A.; Jung, N.; Bach, F.; Ulrich, R.; Neumair, B.; Streit, A.; Bräse, S.
2020. Angewandte Chemie / International edition, 59 (50), 22771–22778. doi:10.1002/anie.202007702

Pollution trace gas distributions and their transport in the Asian monsoon upper troposphere and lowermost stratosphere during the StratoClim campaign 2017
Johansson, S.; Höpfner, M.; Kirner, O.; Wohltmann, I.; Bucci, S.; Legras, B.; Friedl-Vallon, F.; Glatthor, N.; Kretschmer, E.; Ungermann, J.; Wetzel, G.
2020. Atmospheric chemistry and physics, 20 (23), 14695–14715. doi:10.5194/acp-20-14695-2020

Non-stationary spatial regression for modelling monthly precipitation in Germany
Marques, I.; Klein, N.; Kneib, T.
2020. Spatial Statistics, 40, Art.-Nr.: 100386. doi:10.1016/j.spasta.2019.100386

Including residual contact information into replica-exchange MD simulations significantly enriches native-like conformations
Voronin, A.; Weiel, M.; Schug, A.
2020. PLOS ONE, 15 (11), Art.-Nr.: e0242072. doi:10.1371/journal.pone.0242072

Spatio-temporal Structure of the Boundary Layer under the Impact of Mountain Waves
Kalthoff, N.; Adler, B.; Bischoff-Gauss, I.
2020. Meteorologische Zeitschrift, 29 (5), 409–424. doi:10.1127/metz/2020/1033

Workflow Generation with wfGenes
Roozmeh, M.; Kondov, I.
2020. IEEE/ACM Workflows in Support of Large-Scale Science (WORKS), 9–16, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/WORKS51914.2020.00007

On the role of trend and variability in the hydroxyl radical (OH) in the global methane budget
Zhao, Y.; Saunois, M.; Bousquet, P.; Lin, X.; Berchet, A.; Hegglin, M. I.; Canadell, J. G.; Jackson, R. B.; Deushi, M.; Jöckel, P.; Kinnison, D.; Kirner, O.; Strode, S.; Tilmes, S.; Dlugokencky, E. J.; u. a.
2020. Atmospheric chemistry and physics, 20 (21), 13011–13022. doi:10.5194/acp-20-13011-2020

Effective Dynamic Integration and Utilization of Heterogenous Compute Resources
Fischer, M.; Giffels, M.; Heiss, A.; Kuehn, E.; Schnepf, M.; Cube, R. F. von; Petzold, A.; Quast, G.
2020. The European physical journal / Web of Conferences, 245, Article no: 07038. doi:10.1051/epjconf/202024507038

Lightweight dynamic integration of opportunistic resources
Fischer, M.; Kuehn, E.; Giffels, M.; Schnepf, M. J.; Petzold, A.; Heiss, A.
2020. The European physical journal / Web of Conferences, 245, Article no: 07040. doi:10.1051/epjconf/202024507040

Setup and commissioning of a high-throughput analysis cluster
Caspart, R.; Fischer, M.; Giffels, M.; Cube, R. F. von; Heidecker, C.; Kuehn, E.; Quast, G.; Heiss, A.; Petzold, A.
2020. (C. Doglioni, D. Kim, G. A. Stewart, L. Silvestris, P. Jackson & W. Kamleh, Hrsg.) The European physical journal / Web of Conferences, 245, Article no: 07007. doi:10.1051/epjconf/202024507007

Ray Effect Mitigation for the Discrete Ordinates Method Using Artificial Scattering
Frank, M.; Kusch, J.; Camminady, T.; Hauck, C. D.
2020. Nuclear science and engineering, 194 (11), 971–988. doi:10.1080/00295639.2020.1730665

Numerical evaluation of a novel double-concentric swirl burner for sulfur combustion
Zhang, F.; Heidarifatasmi, H.; Harth, S.; Zirwes, T.; Wang, R.; Fedoryk, M.; Sebbar, N.; Habisreuther, P.; Trimis, D.; Bockhorn, H.
2020. Renewable & sustainable energy reviews, 133, Art. Nr.: 110257. doi:10.1016/j.rser.2020.110257

Intrusive acceleration strategies for uncertainty quantification for hyperbolic systems of conservation laws
Kusch, J.; Wolters, J.; Frank, M.
2020. Journal of computational physics, 419, Art. Nr.: 109698. doi:10.1016/j.jcp.2020.109698

Deep Learning, Feature Learning, and Clustering Analysis for SEM Image Classification
Aversa, R.; Coronica, P.; De Nobili, C.; Cozzini, S.
2020. Data Intelligence, 2 (4), 513–528. doi:10.1162/dint_a_00062

Cells in Silico – introducing a high-performance framework for large-scale tissue modeling
Berghoff, M.; Rosenbauer, J.; Hoffmann, F.; Schug, A.
2020. BMC bioinformatics, 21 (1), 436. doi:10.1186/s12859-020-03728-7

Robust Mathematical Formulation and Probabilistic Description of Agent-Based Computational Economic Market Models
Beikirch, M.; Cramer, S.; Frank, M.; Otte, P.; Pabich, E.; Trimborn, T.
2020. Advances in Complex Systems, 23 (6), Art.-Nr.: 2050017. doi:10.1142/S0219525920500174

The Eulerian Stochastic Fields Method Applied to Large Eddy Simulations of a Piloted Flame with Inhomogeneous Inlet
Hansinger, M.; Zirwes, T.; Zips, J.; Pfitzner, M.; Zhang, F.; Habisreuther, P.; Bockhorn, H.
2020. Flow, turbulence and combustion, 105 (3), 837–867. doi:10.1007/s10494-020-00159-5

Numerical Simulations of Turbulent Flame Propagation in a Fan-Stirred Combustion Bomb and Bunsen-Burner at Elevated Pressure
Zhang, F.; Zirwes, T.; Habisreuther, P.; Zarzalis, N.; Bockhorn, H.; Trimis, D.
2020. Flow, turbulence and combustion, 106, 925–944. doi:10.1007/s10494-020-00209-y

Candidate-gene association analysis for a continuous phenotype with a spike at zero using parent-offspring trios
Klein, N.; Entwistle, A.; Rosenberger, A.; Kneib, T.; Bickeböller, H.
2020. Journal of Applied Statistics, 47 (11), 2066–2080. doi:10.1080/02664763.2019.1704226

A velocity-space adaptive unified gas kinetic scheme for continuum and rarefied flows
Xiao, T.; Liu, C.; Xu, K.; Cai, Q.
2020. Journal of computational physics, 415, Art. Nr.: 109535. doi:10.1016/j.jcp.2020.109535

A customized precision format based on mantissa segmentation for accelerating sparse linear algebra
Grützmacher, T.; Cojean, T.; Flegar, G.; Göbel, F.; Anzt, H.
2020. Concurrency and computation, 32 (15), Article: e5418. doi:10.1002/cpe.5418

Multi-scale membrane process optimization with high-fidelity ion transport models through machine learning
Rall, D.; Schweidtmann, A. M.; Kruse, M.; Evdochenko, E.; Mitsos, A.; Wessling, M.
2020. Journal of Membrane Science, 608, Art.-Nr.: 118208. doi:10.1016/j.memsci.2020.118208

Detecting Regime Transitions of the Nocturnal and Polar Near-Surface Temperature Inversion
Kaiser, A.; Faranda, D.; Krumscheid, S.; Belušić, D.; Vercauteren, N.
2020. Journal of the Atmospheric Sciences, 77 (8), 2921–2940. doi:10.1175/JAS-D-19-0287.1

Quantifying uncertain system outputs via the multilevel Monte Carlo method. Part I: Central moment estimation
Krumscheid, S.; Nobile, F.; Pisaroni, M.
2020. Journal of Computational Physics, 414, Article no: 109466. doi:10.1016/j.jcp.2020.109466

Analyse verteilter Daten unter Berücksichtigung von Korrektheit, Skalierbarkeit und Vertraulichkeit. Dissertation
Schlitter, N.
2020, Juli 23. Karlsruher Institut für Technologie (KIT)

Design and Implementation of the first Generic Archive Storage Service for Research Data in Germany
Bach, F.; Schembera, B.; Van Wezel, J.
2020. International Journal of Digital Curation, 15 (1). doi:10.2218/ijdc.v15i1.553

Realizability-preserving discretization strategies for hyperbolic and kinetic equations with uncertainty. Dissertation
Kusch, J.
2020, Juli 14. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000121168

On relaxation systems and their relation to discrete velocity Boltzmann models for scalar advection–diffusion equations
Simonis, S.; Frank, M.; Krause, M. J.
2020. Philosophical transactions of the Royal Society of London / A, 378 (2175), Article: 20190400. doi:10.1098/rsta.2019.0400

NFDI4Chem - Towards a National Research Data Infrastructure for Chemistry in Germany
Steinbeck, C.; Koepler, O.; Bach, F.; Herres-Pawlis, S.; Jung, N.; Liermann, J. C.; Neumann, S.; Razum, M.; Baldauf, C.; Biedermann, F.; Bocklitz, T. W.; Boehm, F.; Broda, F.; Czodrowski, P.; Engel, T.; u. a.
2020. Research ideas and outcomes, (6), e55852, 1–100. doi:10.3897/rio.6.e55852

Directional bivariate quantiles: a robust approach based on the cumulative distribution function
Klein, N.; Kneib, T.
2020. AStA Advances in Statistical Analysis, 104 (2), 225–260. doi:10.1007/s10182-019-00355-3

Robust optimal aiming strategies in central receiver systems
Kuhnke, S.; Richter, P.; Kepp, F.; Cumpston, J.; Koster, A. M. C. A.; Büsing, C.
2020. Renewable energy, 152, 198–207. doi:10.1016/j.renene.2019.11.118

Cold War spy satellite images reveal long-term declines of a philopatric keystone species in response to cropland expansion
Munteanu, C.; Kamp, J.; Nita, M. D.; Klein, N.; Kraemer, B. M.; Müller, D.; Koshkina, A.; Prishchepov, A. V.; Kuemmerle, T.
2020. Proceedings of the Royal Society B: Biological Sciences, 287 (1927), 20192897. doi:10.1098/rspb.2019.2897

Optimization of Procedure for Determining Chlorine Nitrate in the Atmosphere from Ground-Based Spectroscopic Measurements
Virolainen, Y. A.; Polyakov, A. V.; Kirner, O.
2020. Journal of applied spectroscopy, 87 (2), 319–325. doi:10.1007/s10812-020-01002-5

V-FOR-WaTer – the virtual research environment to discover and analyse environmental data
Meyer, J.; Azmi, E.; Hassler, S. K.; Mälicke, M.; Strobl, M.; Zehe, E.
2020. E-Science-Tage 2019: Data to Knowledge. Ed.: V. Heuveline, 199–201, Heidelberger E-Books (heiBOOKS). doi:10.11588/heibooks.598.c8434

Massively Parallel Large-Scale Multi-Model Simulation of Tumour Development Including Treatments
Berghoff, M.; Rosenbauer, J.; Schug, A.
2020. NIC Symposium 2020 : [27-28 February 2020], 63–71, Forschungszentrum Jülich

Modelling regional patterns of inefficiency: A Bayesian approach to geoadditive panel stochastic frontier analysis with an application to cereal production in England and Wales
Klein, N.; Herwartz, H.; Kneib, T.
2020. Journal of Econometrics, 214 (2), 513–539. doi:10.1016/j.jeconom.2019.07.003

Multiscale Tissue Modeling Reveals Impact of Cancer Treatment to Tumor Heterogeneity
Rosenbauer, J.; Berghoff, M.; Schug, A. H.
2020. Biophysical journal, 118 (3), 348a. doi:10.1016/j.bpj.2019.11.2006

Measurement of the integrated luminosity of the Phase 2 data of the Belle II experiment
Belle 2 Collaboration; Abudinén, F.; Adachi, I.; Ahlburg, P.; Aihara, H.; Akopov, N.; Aloisio, A.; Ameli, F.; Andricek, L.; Anh Ky, N.; Asner, D. M.; Atmacan, H.; Aushev, T.; Aushev, V.; Aziz, T.; u. a.
2020. Chinese physics / C, 44 (2), Article: 021001. doi:10.1088/1674-1137/44/2/021001

High-performance data analytics of hybrid rocket fuel combustion data using different machine learning approaches
Debus, C.; Ruettgers, A.; Petrarolo, A.; Kobald, M.; Siggel, M.
2020. AIAA Scitech 2020 Forum, American Institute of Aeronautics and Astronautics. doi:10.2514/6.2020-1161

A Cloud-Based Framework for Machine Learning Workloads and Applications
Lopez Garcia, A.; Tran, V.; Alic, A. S.; Caballer, M.; Plasencia, I. C.; Costantini, A.; Dlugolinsky, S.; Duma, D. C.; Donvito, G.; Gomes, J.; Heredia Cacha, I.; De Lucas, J. M.; Ito, K.; Kozlov, V. Y.; Nguyen, G.; u. a.
2020. IEEE access, 8, 18681–18692. doi:10.1109/ACCESS.2020.2964386

Multivariate Conditional Transformation Models
Kneib, T.; Klein, N.; Hothorn, T.
2020. Proceedings of the 35th International Workshop on Statistical Modelling. Ed.: I. Irigoien, 131–136, Universidad del País Vasco

Enhanced variable selection for distributional regression
Strömer, A.; Weinhold, L.; Staerk, C.; Titze, S.; Klein, N.; Mayr, A.
2020. Proceedings of the 35th International Workshop on Statistical Modelling. Ed.: I. Irigoien, 233–237, Universidad del Pais Vasco

Introducing non-stationarity to wrapped Gaussian spatial responses with an application to wind direction
Marques, I.; Klein, N.; Kneib, T.
2020. Proceedings of the 35th International Workshop on Statistical Modelling. Ed.: I. Irigoien, 159–164, Universidad del País Vasco

Bayesian mixed binary-continuous copula regression with an application to childhood undernutrition
Klein, N.; Kneib, T.; Marra, G.; Radice, R.
2020. Flexible Bayesian Regression Modelling, 121–152, Elsevier. doi:10.1016/B978-0-12-815862-3.00011-1

Mixed discrete‐continuous regression—A novel approach based on weight functions
Michaelis, P.; Klein, N.; Kneib, T.
2020. Stat, 9 (1), Art.-Nr.: e277. doi:10.1002/sta4.277

Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol
Bach, P.; Wallisch, C.; Klein, N.; Hafermann, L.; Sauerbrei, W.; Steyerberg, E. W.; Heinze, G.; Rauch, G.
2020. (R. Bender, Hrsg.) PLOS ONE, 15 (12), e0241427. doi:10.1371/journal.pone.0241427

The GridKa Tape Storage: various performance test results and current improvements
Musheghyan, H.; Petzold, A.; Heiss, A.; Ressmann, D.; Beitzinger, M.
2020. EPJ Web of Conferences, 245, Art.-Nr.: 04026. doi:10.1051/epjconf/202024504026

bwDIM - Data In Motion
Bach, F.; Ulrich, R.
2020. E-Science-Tage 2019: Data to Knowledge. Hrsg.: V. Heuveline, 248–249, Universitätsbibliothek Heidelberg. doi:10.11588/heidok.00026842

SuLMaSS - Sustainable Lifecycle Management for Scientific Software
Loewe, A.; Seemann, G.; Wülfers, E. M.; Huang, Y.-L.; Sánchez, J.; Bach, F.; Ulrich, R.; Selzer, M.
2020. E-Science-Tage 2019 : data to knowledge. Hrsg.: V. Heuveline, 238–240, Universitätsbibliothek Heidelberg

Bedarfsgerechte Weiterentwicklung von RADAR als Forschungsdaten-Repositorium für das KIT
Bach, F.; Soltau, K.; Razum, M.
2020. E-Science-Tage 2019: Data to Knowledge. Hrsg.: V. Heuveline, 162–172, Universitätsbibliothek Heidelberg

HeAT - A Distributed and GPU-accelerated Tensor Framework for Data Analytics
Götz, M.; Debus, C.; Coquelin, D.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. 2020 IEEE International Conference on Big Data (Big Data): 10-13 December 2020, online, 276–287, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData50022.2020.9378050

Studies of X(3872) and ψ(2S) production in collisions at 1.96 TeV
D0 Collaboration; Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Aushev, V.; Aushev, Y.; u. a.
2020. Physical review / D, 102 (7), Art.-Nr.: 072005. doi:10.1103/PhysRevD.102.072005

X-CEL: A Method to Estimate Near-Memory Acceleration Potential in Tile-Based MPSoCs
Rheindt, S.; Fried, A.; Lenke, O.; Nolte, L.; Sabirov, T.; Twardzik, T.; Wild, T.; Herkersdorf, A.
2020. Architecture of Computing Systems – ARCS 2020 – 33rd International Conference, Aachen, Germany, May 25–28, 2020, Proceedings. Ed.: A. Brinkmann, 109–123, Springer International Publishing. doi:10.1007/978-3-030-52794-5_9

Sparse Linear Algebra on AMD and NVIDIA GPUs – The Race Is On
Tsai, Y. M.; Cojean, T.; Anzt, H.
2020. High Performance Computing – 35th International Conference, ISC High Performance 2020, Frankfurt/Main, Germany, June 22–25, 2020, Proceedings. Ed.: P. Sadayappan, 309–327, Springer International Publishing. doi:10.1007/978-3-030-50743-5_16

IPv6-only networking on WLCG
Babik, M.; Bly, M.; Chown, T.; Christidis, D.; Chudoba, J.; Condurache, C.; Finnern, T.; Froy, T.; Grigoras, C.; Hafeez, K.; Hoeft, B.; Kelsey, D.; Lopes, R.; López Muñoz, F.; Martelli, E.; u. a.
2020. The European physical journal / Web of Conferences, 245, Art.-Nr.: 07045. doi:10.1051/epjconf/202024507045

Unroutable Traffic: Maintaining Trust and Integrity of the LHC Open Network Environment
Hoeft, B.; Ambroj Pérez, S.; Bergroth, M.; O’Connor, M.; Cziva, R.
2020. The European physical journal / Web of Conferences, 245, Art.-Nr.: 07018. doi:10.1051/epjconf/202024507018

Predicting resource usage for enhanced job scheduling for opportunistic resources in HEP
Kuehn, E.; Fischer, M.; Lange, S.; Petzold, A.; Heiss, A.
2020. The European physical journal / Web of Conferences, 245, Article no: 07039. doi:10.1051/epjconf/202024507039

Development of an Openfoam Solver for Numerical Simulation of Carbonization of Biomasses in Rotary Kilns
Tavakkol, S.; Zirwes, T.; Denev, J. A.; Jamshidi, F.; Bockhorn, H.
2020. OpenFOAM Workshop, June 22 - 25, 2020, Arlington, Virginia, USA

Aristoteles annotieren - Vom Handschriftendigitalisat zur qualitativ-quantitativen Annotation
Götzelmann, G.; Tonne, D.
2020. Bilddaten in den Digitalen Geisteswissenschaften. Hrsg.: C. Hastik, 53–66, Harrassowitz Verlag

Validation study for Large-Eddy Simulation of Forest Flow
Pitchurov, G.; Gromke, C.; Denev, J. A.; Cesar Cunha Galeazzo, F.
2020. E3S Web of Conferences, 207, Art.-Nr.: 02010. doi:10.1051/e3sconf/202020702010

Design of Metal-Organic Framework Templated Materials Using High-Throughput Computational Screening
Ahmad, M.; Luo, Y.; Wöll, C.; Tsotsalas, M.; Schug, A.
2020. Molecules, 25 (21), 4875. doi:10.3390/molecules25214875

Structure and properties of MgB2bulks: Ab-initio simulations compared to experiment
Romaka, V. V.; Prikhna, T. A.; Eisterer, M.; Shapovalov, A. P.; Goldacker, W.; Moshchil, V. E.; Kozyrev, A.; Rindfleisch, M.; Tompsic, M.; Hellstrom, E. E.; Grechnev, G. E.; Zhang, V. S.; Yang, F.; Li, C.
2020. IOP conference series / Materials science and engineering, 756 (1), Art. Nr.: 012020. doi:10.1088/1757-899X/756/1/012020

Loss Scheduling for Class-Imbalanced Segmentation Problems
Taubert, O.; Götz, M.; Schug, A.; Streit, A.
2020. 19th IEEE International Conference on Machine Learning and Applications (ICMLA), 422–427, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICMLA51294.2020.00073

HeAT – a Distributed and GPU-accelerated TensorFramework for Data Analytics
Götz, M.; Debus, C.; Coquelin, D.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. 2020 IEEE International Conference on Big Data (Big Data), 276–287, Institute of Electrical and Electronics Engineers (IEEE)

Walltime Prediction and Its Impact on Job Scheduling Performance and Predictability
Klusáček, D.; Soysal, M.
2020. Job Scheduling Strategies for Parallel Processing. Ed.: D. Klusáček, 127–144, Springer

ADA-FS - Advanced Data Placement via Ad hoc File Systems at Extreme Scales
Oeste, S.; Vef, M.-A.; Soysal, M.; Nagel, W. E.; Brinkmann, A.; Streit, A.
2020. Software for Exascale Computing-SPPEXA 2016-2019. Ed.: H.-J. Bungartz, 29–59, Springer. doi:10.1007/978-3-030-47956-5_4

CoExDBSCAN: Density-based Clustering with Constrained Expansion
Ertl, B.; Meyer, J.; Schneider, M.; Streit, A.
2020. Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. Ed.: A. Fred. Vol. 1, 104–115, SciTePress. doi:10.5220/0010131201040115

The whole is greater than the sum of its parts analyzing aristotle commentaries in collaboration between philology and data science
Krewet, M.; Tonne, D.; Götzelmann, G.; Hegel, P.; Soring, S.
2020. Twin Talks: Understanding and Facilitating Collaboration in Digital Humanities 2020: Proceedings of the Twin Talks 2 and 3 Workshops at DHN 2020 and DH 2020. Ed.: S. Krauwer, 103–114, RWTH Aachen

Using HEP experiment workflows for the benchmarking and accounting of WLCG computing resources
Valassi, A.; Alef, M.; Barbet, J.-M.; Datskova, O.; De Maria, R.; Fontes Medeiros, M.; Giordano, D.; Grigoras, C.; Hollowell, C.; Javurkova, M.; Khristenko, V.; Lange, D.; Michelotto, M.; Rinaldi, L.; Sciabà, A.; u. a.
2020. The European physical journal / Web of Conferences, 245, Art.-Nr.: 07035. doi:10.1051/epjconf/202024507035

Adaptive clustering: reducing the computational costs of distributed (hydrological) modelling by exploiting time-variable similarity among model elements
Ehret, U.; Pruijssen, R. van; Bortoli, M.; Loritz, R.; Azmi, E.; Zehe, E.
2020. Hydrology and earth system sciences, 24 (9), 4389–4411. doi:10.5194/hess-24-4389-2020

Modeling of Wnt-mediated tissue patterning in vertebrate embryogenesis
Rosenbauer, J.; Zhang, C.; Mattes, B.; Reinartz, I.; Wedgwood, K.; Schindler, S.; Sinner, C.; Scholpp, S.; Schug, A.
2020. (A. R. Asthagiri, Hrsg.) PLoS Computational Biology, 16 (6), e1007417. doi:10.1371/journal.pcbi.1007417

Evolutionary Approach of Clustering to Optimize Hydrological Simulations
Azmi, E.; Strobl, M.; Pruijssen, R. van; Ehret, U.; Meyer, J.; Streit, A.
2020. Computational Science and Its Applications – ICCSA 2020 – 20th International Conference, Cagliari, Italy, July 1–4, 2020, Proceedings, Part I. Ed.: O. Gervasi, 617–633, Springer. doi:10.1007/978-3-030-58799-4_45

DNS-studies on flame front markers for turbulent premixed combustion
Schieβl R.; Denev, J. A.
2020. Combustion theory and modelling, 24 (6), 983–1001. doi:10.1080/13647830.2020.1800102

Multiprecision Block-Jacobi for iterative triangular solves
Goebel, F.; Anzt, H.; Cojean, T.; Flegar, G.; Quintana-Ortí, E. S.
2020. Lecture notes in computer science, 546–560, Springer. doi:10.1007/978-3-030-57675-2_34

Annotationen und ihre infrastrukturellen Prämissen
Hegel, P.; Götzelmann, G.; Krewet, M.; Tonne, D.
2020. Digital Humanities Austria 2018 : Empowering Researchers. Hrsg.: M. Ernst, 150–153, Austrian Academy of Sciences Press. doi:10.1553/dha-proceedings2018s1

DHd 2020 Spielräume: Digital Humanities zwischen Modellierung und Interpretation. Konferenzabstracts
Schöch, C.
2020. Zenodo. doi:10.5281/zenodo.3666690

Volltexte – die Zukunft alter Drucke: Bericht zum Abschlussworkshop des OCR-D-Projekts
Engl, E.; Boenig, M.; Baierer, K.; Hartmann, V.; Neudecker, C.
2020. O-bib, 7 (2), 1–4. doi:10.5282/O-BIB/5600

Projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence
Amos, M.; Young, P. J.; Hosking, J. S.; Lamarque, J.-F.; Abraham, N. L.; Akiyoshi, H.; Archibald, A. T.; Bekki, S.; Deushi, M.; Jöckel, P.; Kinnison, D.; Kirner, O.; Kunze, M.; Marchand, M.; Plummer, D. A.; u. a.
2020. Atmospheric chemistry and physics, 20 (16), 9961–9977. doi:10.5194/acp-20-9961-2020

A low-rank method for two-dimensional time-dependent radiation transport calculations
Peng, Z.; McClarren, R. G.; Frank, M.
2020. Journal of computational physics, 421, Art.-Nr.: 109735. doi:10.1016/j.jcp.2020.109735

Oxygen Evolution and Reduction on Fe-doped NiOOH: Influence of Solvent, Dopant Position and Reaction Mechanism
Vandichel, M.; Laasonen, K.; Kondov, I.
2020. Topics in catalysis, 63, 833–845. doi:10.1007/s11244-020-01334-8

Federation of compute resources available to the German CMS community
Cube, R. F. von; Giffels, M.; Heidecker, C.; Quast, G.; Sauter, M. B.; Schnepf, M. J.
2020. Journal of physics / Conference series, 1525 (1), Art. Nr.: 012055. doi:10.1088/1742-6596/1525/1/012055

Boosting Performance of Data-intensive Analysis Workflows with Distributed Coordinated Caching
Heidecker, C.; Cube, R. F. von; Giffels, M.; Quast, G.; Sauter, M.; Schnepf, M. J.
2020. Journal of physics / Conference series, 1525 (1), Art. Nr.: 012065. doi:10.1088/1742-6596/1525/1/012065

HEP Analyses on Dynamically Allocated Opportunistic Computing Resources
Schnepf, M. J.; Cube, R. F. von; Heidecker, C.; Fischer, M.; Giffels, M.; Kuehn, E.; Heiss, A.; Petzold, A.; Quast, G.; Sauter, M.
2020. Journal of physics / Conference series, 1525 (1), Art. Nr.: 012067. doi:10.1088/1742-6596/1525/1/012067

Emerging Tumor Development by Simulating Single-cell Events [submitted]
Rosenbauer, J.; Berghoff, M.; Schug, A.
2020. bioRxiv beta. doi:10.1101/2020.08.24.264150

Pax6 organizes the anterior eye segment by guiding two distinct neural crest waves
Takamiya, M.; Stegmaier, J.; Kobitski, A. Y.; Schott, B.; Weger, B. D.; Margariti, D.; Cereceda Delgado, A. R.; Gourain, V.; Scherr, T.; Yang, L.; Sorge, S.; Otte, J. C.; Hartmann, V.; Wezel, J. van; Stotzka, R.; u. a.
2020. PLoS Genetics, 16 (6), Art. Nr.: e1008774. doi:10.1371/journal.pgen.1008774

An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action
Anzt, H.; Bach, F.; Druskat, S.; Löffler, F.; Loewe, A.; Renard, B. Y.; Seemann, G.; Struck, A.; Achhammer, E.; Aggarwal, P.; Appel, F.; Bader, M.; Brusch, L.; Busse, C.; Chourdakis, G.; u. a.
2020. F1000Research, 9, Article no: 295. doi:10.12688/f1000research.23224.1

Evaluating DCA-based method performances for RNA contact prediction by a well-curated data set
Pucci, F.; Zerihun, M. B.; Peter, E. K.; Schug, A.
2020. RNA, 26 (7), 794–802. doi:10.1261/rna.073809.119

Pcdh18a regulates endocytosis of E-cadherin during axial mesoderm development in zebrafish
Bosze, B.; Ono, Y.; Mattes, B.; Sinner, C.; Gourain, V.; Thumberger, T.; Tlili, S.; Wittbrodt, J.; Saunders, T. E.; Strähle, U.; Schug, A.; Scholpp, S.
2020. Histochemistry and cell biology, 154, 463–480. doi:10.1007/s00418-020-01887-5

Massively Parallel Stencil Strategies for Radiation Transport Moment Model Simulations
Berghoff, M.; Frank, M.; Seibold, B.
2020. Computational Science – ICCS 2020 : 20th International Conference, Amsterdam, The Netherlands, June 3–5, 2020. Proceedings. Part 7. Ed.: V. Krzhizhanovskaya, 242–256, Springer Nature. doi:10.1007/978-3-030-50436-6_18

Load-balancing Sparse Matrix Vector Product Kernels on GPUs
Anzt, H.; Cojean, T.; Yen-Chen, C.; Dongarra, J.; Flegar, G.; Nayak, P.; Tomov, S.; Tsai, Y. M.; Wang, W.
2020. ACM Transactions on Parallel Computing, 7 (1), Article: 2. doi:10.1145/3380930

Acceleration of PageRank with Customized Precision Based on Mantissa Segmentation
Grützmacher, T.; Cojean, T.; Flegar, G.; Anzt, H.; Quintana-Ortí, E. S.
2020. ACM Transactions on Parallel Computing, 7 (1), Article: 4. doi:10.1145/3380934

pydca v1.0: a comprehensive software for direct coupling analysis of RNA and protein sequences
Zerihun, M. B.; Pucci, F.; Peter, E. K.; Schug, A.
2020. Bioinformatics, 36 (7), 2264–2265. doi:10.1093/bioinformatics/btz892

Theoretical background of the hybrid VπLES method for flows with variable transport properties
Kornev, N.; Denev, J.; Samarbakhsh, S.
2020. Fluids, 5 (2), Article: 45. doi:10.3390/fluids5020045

Alea – Complex Job Scheduling Simulator
Klusáček, D.; Soysal, M.; Suter, F.
2020. Parallel Processing and Applied Mathematics - 13th International Conference, PPAM 2019, Bialystok, Poland, September 8–11, 2019, Revised Selected Papers, Part II. Hrsg.: R. Wyrzykowski, 217–229, Springer International Publishing. doi:10.1007/978-3-030-43222-5_19

Computational Study on Small Pt Clusters: Structure of Pt Clusters and Elementary Steps in Nanocatalysis. Dissertation
Yohannes, A. G.
2020. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000105273

Compression Methods for Structured Floating-Point Data and their Application in Climate Research. Dissertation
Çayoğlu, U.
2020. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000105055

Filtered stochastic Galerkin methods for hyperbolic equations
Kusch, J.; McClarren, R. G.; Frank, M.
2020. Journal of computational physics, 403, Article No.109073. doi:10.1016/j.jcp.2019.109073

Quasi-DNS Dataset of a Piloted Flame with Inhomogeneous Inlet Conditions
Zirwes, T.; Zhang, F.; Habisreuther, P.; Hansinger, M.; Bockhorn, H.; Pfitzner, M.; Trimis, D.
2020. Flow, turbulence and combustion, 104, 997–1027. doi:10.1007/s10494-019-00081-5

A structured approach to the construction of stable linear Lattice Boltzmann collision operator
Otte, P.; Frank, M.
2020. Computers and mathematics with applications, 79 (5), 1447–1460. doi:10.1016/j.camwa.2019.09.009

Belle II pixel detector: Performance of final DEPFET modules
Paschen, B.; Abudinen, F.; Ackermann, K.; Ahlburg, P.; Albalawi, M.; Alonso, O.; Andricek, L.; Ayad, R.; Babu, V.; Bai, Y.; Bilka, T.; Blanco, R.; Boronat, M.; Bozek, A.; Camien, C.; u. a.
2020. (Collaboration, PXD, Hrsg.) Nuclear instruments & methods in physics research / A, 958, Article No.162222. doi:10.1016/j.nima.2019.05.063

diSTruct v1.0: generating biomolecular structures from distance constraints
Taubert, O.; Reinartz, I.; Meyerhenke, H.; Schug, A.
2019. Bioinformatics, 35 (24), 5337–5338. doi:10.1093/bioinformatics/btz578

Implicit Copulas from Bayesian Regularized Regression Smoothers
Klein, N.; Smith, M. S.
2019. Bayesian Analysis, 14 (4), 1143–1171. doi:10.1214/18-BA1138

Concentration dependent energy levels shifts in donor-acceptor mixtures due to intermolecular electrostatic interaction
Bag, S.; Friederich, P.; Kondov, I.; Wenzel, W.
2019. Scientific reports, 9 (1), Art. Nr.: 12424. doi:10.1038/s41598-019-48877-9

Assessing the relationship between markers of glycemic control through flexible copula regression models
Espasandín-Domínguez, J.; Cadarso-Suárez, C.; Kneib, T.; Marra, G.; Klein, N.; Radice, R.; Lado-Baleato, O.; González-Quintela, A.; Gude, F.
2019. Statistics in Medicine, 38 (27), 5161–5181. doi:10.1002/sim.8358

Central limit theorems for multilevel Monte Carlo methods
Hoel, H.; Krumscheid, S.
2019. Journal of Complexity, 54, Art.-Nr.: 101407. doi:10.1016/j.jco.2019.05.001

Direct coupling analysis improves the identification of beneficial amino acid mutations for the functional thermostabilization of a delicate decarboxylase
Peng, M.; Maier, M.; Esch, J.; Schug, A.; Rabe, K. S.
2019. Biological chemistry, 400 (11), 1519–1527. doi:10.1515/hsz-2019-0156

Multivariate effect priors in bivariate semiparametric recursive Gaussian models
Thaden, H.; Klein, N.; Kneib, T.
2019. Computational Statistics & Data Analysis, 137, 51–66. doi:10.1016/j.csda.2018.12.004

An adaptive quadrature-based moment closure
Kusch, J.; Frank, M.
2019. International journal of advances in engineering sciences and applied mathematics, 11 (3), 174–186. doi:10.1007/s12572-019-00252-7

Impact of Combustion Modeling on the Spectral Response of Heat Release in LES
Zhang, F.; Zirwes, T.; Habisreuther, P.; Bockhorn, H.; Trimis, D.; Nawroth, H.; Paschereit, C. O.
2019. Combustion science and technology, 191 (9), 1520–1540. doi:10.1080/00102202.2018.1558218

Aspekte digitaler Infrastrukturen : Forschungsdaten im Sonderforschungsbereich 980 „Episteme in Bewegung“: Herausforderungen und Perspektiven
Götzelmann, G.; Hegel, P.; Krewet, M.; Söring, S.; Tonne, D.
2019. Bibliothek Forschung und Praxis, 43 (2), 324–331. doi:10.1515/bfp-2019-2055

Towards Continuous Benchmarking – An Automated Performance Evaluation Framework for High Performance Software
Anzt, H.; Chen, Y.-C.; Cojean, T.; Dongarra, J.; Flegar, G.; Nayak, P.; Quintana-Ortí, E. S.; Tsai, Y. M.; Wang, W.
2019. Proceedings of the Platform for Advanced Scientific Computing Conference, Article no: 9, Association for Computing Machinery (ACM). doi:10.1145/3324989.3325719

Simulation and Analysis of Protein-Fluorophore Systems for Comparison with Fluorescence Spectroscopy Data. Dissertation
Reinartz, I.
2019, Juni 11. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000095718

Wie gelingt digitalisierte Forschung? Neues Open Source ELN für die Wissenschaft
Jung, N.; Tremouilhac, P.; Bach, F.; Kramer, C.; Bräse, S.; Ottleben, I.
2019. Labor-Praxis

Quantifying uncertainties in contact mechanics of rough surfaces using the multilevel Monte Carlo method
Rey, V.; Krumscheid, S.; Nobile, F.
2019. International Journal of Engineering Science, 138, 50–64. doi:10.1016/j.ijengsci.2019.02.003

Numerical prediction of air-assisted primary atomization using Smoothed Particle Hydrodynamics
Braun, S.; Wieth, L.; Holz, S.; Dauch, T. F.; Keller, M. C.; Chaussonnet, G.; Gepperth, S.; Koch, R.; Bauer, H.-J.
2019. International journal of multiphase flow, 114, 303–315. doi:10.1016/j.ijmultiphaseflow.2019.03.008

On charge percolation in slurry electrodes used in vanadium redox flow batteries
Lohaus, J.; Rall, D.; Kruse, M.; Steinberger, V.; Wessling, M.
2019. Electrochemistry Communications, 101, 104–108. doi:10.1016/j.elecom.2019.02.013

Rejoinder on: Modular regression - a Lego system for building structured additive distributional regression models with tensor product interactions
Kneib, T.; Klein, N.; Lang, S.; Umlauf, N.
2019. TEST, 28 (1), 55–59. doi:10.1007/s11749-019-00636-8

Modular regression - a Lego system for building structured additive distributional regression models with tensor product interactions
Kneib, T.; Klein, N.; Lang, S.; Umlauf, N.
2019. TEST, 28 (1), 1–39. doi:10.1007/s11749-019-00631-z

Adaptive precision in block-Jacobi preconditioning for iterative sparse linear system solvers
Anzt, H.; Dongarra, J.; Flegar, G.; Higham, N. J.; Quintana-Ortí, E. S.
2019. Concurrency and computation, 31 (6), e4460. doi:10.1002/cpe.4460

Mixed binary‐continuous copula regression models with application to adverse birth outcomes
Klein, N.; Kneib, T.; Marra, G.; Radice, R.; Rokicki, S.; McGovern, M. E.
2019. Statistics in Medicine, 38 (3), 413–436. doi:10.1002/sim.7985

Gaussian Process Responses in Distributional Regression
Riebl, H.; Klein, N.; Kneib, T.
2019. Proceedings of the 34th International Workshop on Statistical Modelling. Ed.: L.M. Machado. Vol. 2, 341–345, Statistical Modelling Society

Non-Stationary Spatial Regression for Modelling Monthly Precipitation in Germany
Marques, I.; Klein, N.; Kneib, T.
2019. Proceedings of the 34th International Workshop on Statistical Modelling. Vol 2. Ed.: L. Meira-Machado, 195–199

Modular Regression – A Lego System for Building Structured Additive Distributional Regression Models with Tensor Product Interactions
Kneib, T.; Klein, N.; Umlauf, N.; Lang, S.
2019. Proceedings of the 34th International Workshop on Statistical Modelling. Vol 1. Ed.: L. Meira-Machado, 214–219

Neural Network Regression with an Application to Leukaemia Survival Data – An Unstructured Distributional Approach
Klein, N.; Umlauf, N.; Simon, T.
2019. Proceedings of the 34th International Workshop on Statistical Modelling. Vol 1. Ed.: L. Meira-Machado, 157–160

Density regression via penalised splines dependent Dirichlet process mixture of normal models
Carvalho, V. de; Rodríguez-Álvarez, M.; Klein, N.
2019. Proceedings of the 34th International Workshop on Statistical Modelling. Vol 1. Ed.: L. Meira-Machado, 184–188

MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging–design, implementation and application on the example of DCE-MRI
Debus, C.; Floca, R.; Ingrisch, M.; Kompan, I.; Maier-Hein, K.; Abdollahi, A.; Nolden, M.
2019. BMC bioinformatics, 20 (1), Artkl.Nr.: 31. doi:10.1186/s12859-018-2588-1

An der Schnittstelle von Fach-und Informationswissenschaft : Das INF-Projekt des SFB 980 "Episteme in Bewegung : Wissenstransfers von der Alten Welt bis in die frühe Neuzeit”
Söring, S.; Götzelmann, G.; Hegel, P.; Krewet, M.; Tonne, D.
2019. Bausteine Forschungsdatenmanagement, (2, SH), 89–95. doi:10.17192/bfdm.2019.2.8083

Aristoteles auf Reisen : Handschriftenforschung in der digitalen Infrastruktur des SFB 980 „Episteme in Bewegung“
Krewet, M.; Hegel, P.; Götzelmann, G.; Tonne, D.; Söring, S.
2019. Forschungsinfrastrukturen in den digitalen Geisteswissenschaften : Wie verändern digitale Infrastrukturen die Praxis der Geisteswissenschaften? Hrsg.: M. Huber, 77–87, DFG

OCR-D: An end-to-end open source OCR framework for historical printed documents
Neudecker, C.; Baierer, K.; Federbusch, M.; Boenig, M.; Würzner, K.-M.; Hartmann, V.; Herrmann, E.
2019. EuropeanaTech Insight, 13

German-Russian astroparticle data life cycle initiative
Haungs, A.; Bychkov, I.; Dubenskaya, J.; Fedorov, O.; Heiss, A.; Kang, D.; Kazarina, Y.; Korosteleva, E.; Kostunin, D.; Kryukov, A.; Mikhailov, A.; Nguyen, M.-D.; Polgart, F.; Polyakov, S.; Postnikov, E.; u. a.
2019. 36th International Cosmic Ray Conference (ICRC 2019), Madison, WI, USA, 24.07.2019 – 01.08.2019. doi:10.22323/1.358.0284

Adoption of ARC-CE and HTCondor at GridKa Tier 1
Fischer, M.; Kuehn, E.; Schnepf, M.; Petzold, A.; Heiss, A.
2019. The European physical journal / Web of Conferences, 214, Art.-Nr.: 03053. doi:10.1051/epjconf/201921403053

Complex modeling: Does climate change really exist? – Perspectives of a project day with high school students
Hattebuhr, M.; Frank, M.
2019. 11th Congress of the European Society for Researchin Mathematics Education

Parallel selection on GPUs
Ribizel, T.; Anzt, H.
2019. Parallel computing, 91, Article: 102588. doi:10.1016/j.parco.2019.102588

A Positive Asymptotic-Preserving Scheme for Linear Kinetic Transport Equations
Laiu, M. P.; Frank, M.; Hauck, C. D.
2019. SIAM journal on scientific computing, 41 (3), A1500–A1526. doi:10.1137/18M1196297

Dynamic Integration and Management of Opportunistic Resources for HEP
Schnepf, M. J.; Cube, R. F. von; Fischer, M.; Giffels, M.; Heidecker, C.; Heiss, A.; Kuehn, E.; Petzold, A.; Quast, G.; Sauter, M.
2019. The European physical journal / Web of Conferences, 214, 08009. doi:10.1051/epjconf/201921408009

Advancing throughput of HEP analysis work-flows using caching concepts
Caspart, R.; Fischer, M.; Giffels, M.; Heidecker, C.; Kühn, E.; Quast, G.; Sauter, M.; Schnepf, M. J.; Cube, R. F. von
2019. The European physical journal / Web of Conferences, 214, Article no: 04007. doi:10.1051/epjconf/201921404007

Book of Abstracts: Sixth bwHPC Symposium, 30 September 2019, Karlsruhe, Germany
Denev, J.; Barthel, R.; Frank, M. (Hrsg.)
2019. Karlsruher Institut für Technologie (KIT)

A low-rank method for time-dependent transport calculations
Peng, Z.; McClarren, R. G.; Frank, M.
2019. International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C), Portland, OR, August 25-29, 2019, 957–966, American Nuclear Society (ANS)

Ray-effect mitigation for the discrete ordinates method using artificial scattering
Camminady, T.; Frank, M.; Hauck, C. D.; Kusch, J.
2019. International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C), Portland, OR, August 25-29, 2019, 459–466, American Nuclear Society (ANS)

Highly uniform quadrature sets for the discrete ordinates method
Camminady, T.; Frank, M.; Kusch, J.
2019. International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C), Portland, OR, August 25-29, 2019, 449–458, American Nuclear Society (ANS)

Intrusive uncertainty quantification for applications in fluid dynamics
Kusch, J.; Wolters, J.; Frank, M.
2019. International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C), Portland, OR, August 25-29, 2019, 1918–1927, American Nuclear Society (ANS)

Benchmarking Deep Learning Infrastructures by Means of TensorFlow and Containers
Grupp, A.; Kozlov, V.; Campos, I.; David, M.; Gomes, J.; López García, Á.
2019. High Performance Computing : ISC High Performance 2019 International Workshops, Frankfurt, Germany, June 16-20, 2019. Ed.: M. Weiland, 478–489, Springer International Publishing. doi:10.1007/978-3-030-34356-9_36

Towards Seamless Simulations of Polar Stratospheric Clouds and Ozone in the Polar Stratosphere with ICON-ART. Dissertation
Weimer, M.
2019. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000100338

ParILUT - A parallel threshold ILU for GPUS
Anzt, H.; Ribizel, T.; Flegar, G.; Chow, E.; Dongarra, J.
2019. Proceedings 2019 IEEE 33rd International Parallel and Distributed Processing Symposium, IPDPS 2019: 20-24 May 2019, Rio de Janeiro, Brazil, 231–241, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IPDPS.2019.00033

Inter-model comparison of global hydroxyl radical (OH) distributions and their impact on atmospheric methane over the 2000-2016 period
Zhao, Y.; Saunois, M.; Bousquet, P.; Lin, X.; Berchet, A.; Hegglin, M. I.; Canadell, J. G.; Jackson, R. B.; Hauglustaine, D. A.; Szopa, S.; Stavert, A. R.; Abraham, N. L.; Archibald, A. T.; Bekki, S.; Deushi, M.; u. a.
2019. Atmospheric chemistry and physics, 19 (21), 13701–13723. doi:10.5194/acp-19-13701-2019

PAPI software-defined events for in-depth performance analysis
Jagode, H.; Danalis, A.; Anzt, H.; Dongarra, J.
2019. The international journal of high performance computing applications, 33 (6), 1113–1127. doi:10.1177/1094342019846287

Data Encoding in Lossless Prediction-Based Compression Algorithms
Cayoglu, U.; Tristram, F.; Meyer, J.; Schröter, J.; Kerzenmacher, T.; Braesicke, P.; Streit, A.
2019. IEEE 15th International Conference on eScience : 24-27 September 2019, San Diego, California : proceedings. Ed.: Ilkay Altintas, 226–234, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/eScience.2019.00032

On Advancement of Information Spaces to Improve Prediction-Based Compression
Cayoglu, U.; Tristram, F.; Meyer, J.; Kerzenmacher, T.; Braesicke, P.; Streit, A.
2019. INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft Hrsg.: K. David, 271–272, Gesellschaft für Informatik (GI). doi:10.18420/inf2019_39

Enlargement of Submicron Gas‐Borne Particles by Heterogeneous Condensation for Energy‐Efficient Aerosol Separation
Hamberger, P.; Koch, D. P.; Sinanis, S.; Schaber, K.
2019. Chemical engineering & technology, 42 (11), 2458–2464. doi:10.1002/ceat.201800720

Application of Mixtures of Gaussians for Tracking Clusters in Spatio-temporal Data
Ertl, B.; Meyer, J.; Streit, A.; Schneider, M.
2019. Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, September 17-19, 2019, in Vienna, Austria, Vol. 1. Ed.: A. Fred, 45–54, SciTePress. doi:10.5220/0007949700450054

Algorithm Selection in Auction-based Allocation of Cloud Computing Resources. Dissertation
Gudu, D.
2019. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000098816

Portfolio optimization and model predictive control: A kinetic approach
Trimborn, T.; Pareschi, L.; Frank, M.
2019. Discrete and continuous dynamical systems / B, 24 (11), 6209–6238. doi:10.3934/dcdsb.2019136

Numerical and Experimental Investigations of Primary Breakup of High-Viscous Fluid at Elevated Pressure [in press]
Zhang, F.; Zirwes, T.; Wachter, S.; Jakobs, T.; Habisreuther, P.; Zarzalis, N.; Dimosthenis, T.; Kolb, T.
2019. 29th European Conference on Liquid Atomization and Spray Systems, Paris, 2-4 Sep 2019

Federated Identity Management for Research
WISE SCI Working Group; Barton, T.; Gietz, P.; Kelsey, D.; Koranda, S.; Short, H.; Stevanovic, U.
2019. (A. Forti, L. Betev, M. Litmaath, O. Smirnova & P. Hristov, Hrsg.) The European physical journal / Web of Conferences, 214, Art.Nr.: 03044. doi:10.1051/epjconf/201921403044

The effect of atmospheric nudging on the stratospheric residual circulation in chemistry–climate models
Chrysanthou, A.; Maycock, A. C.; Chipperfield, M. P.; Dhomse, S.; Garny, H.; Kinnison, D.; Akiyoshi, H.; Deushi, M.; Garcia, R. R.; Jöckel, P.; Kirner, O.; Pitari, G.; Plummer, D. A.; Revell, L.; Rozanov, E.; u. a.
2019. Atmospheric chemistry and physics, 19 (17), 11559–11586. doi:10.5194/acp-19-11559-2019

Next Generation of HEP CPU Benchmarks
Giordano, D.; Alef, M.; Michelotto, M.
2019. The European physical journal / Web of Conferences, 214, Article no: 08011. doi:10.1051/epjconf/201921408011

Optimization of robust aiming strategies in solar tower power plants
Richter, P.; Kepp, F.; Büsing, C.; Kuhnke, S.
2019. SolarPACES 2018. Ed.: C. Richter, 030045, American Institute of Physics (AIP). doi:10.1063/1.5117557

Are we doing the right thing? - A critical analysis of the academic HPC community
Anzt, H.; Flegar, G.
2019. 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 739–745, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IPDPSW.2019.00122

Approximate and exact selection on GPUs
Ribizel, T.; Anzt, H.
2019. 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 471–478, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IPDPSW.2019.00088

Clear-sky ultraviolet radiation modelling using output from the Chemistry Climate Model Initiative
Lamy, K.; Portafaix, T.; Josse, B.; Brogniez, C.; Godin-Beekmann, S.; Bencherif, H.; Revell, L.; Akiyoshi, H.; Bekki, S.; Hegglin, M. I.; Jöckel, P.; Kirner, O.; Liley, B.; Marecal, V.; Morgenstern, O.; u. a.
2019. Atmospheric chemistry and physics, 19 (15), 10087–10110. doi:10.5194/acp-19-10087-2019

Unsteady pure straining effects on lean premixed flames of different Lewis numbers
Denev, J. A.; Naydenova, I.; Zhang, F.; Zirwes, T.; Bockhorn, H.
2019. 9th European Combustion Meeting (ECM), Lissabon, Portugal, 14 - 17 April 2019

2D and 3D numerical simulation of chemiluminescent radical concentrations during side-wall quenching of premixed methane and propane flames [in press]
Zirwes, T.; Häber, T.; Zhang, F.; Kosaka, H.; Bockhorn, H.; Suntz, R.; Dreizler, A.; Janicka, J.
2019. 9th European Combustion Meeting (ECM), Lissabon, Portugal, 14 - 17 April 2019

Neues Konzept zur skalierbaren, explorativen Analyse großer Zeitreihendaten mit Anwendung auf umfangreiche Stromnetz-Messdaten. Dissertation
Bach, F.
2019. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000097843

Numerical simulation of sulfur combustors with high-power-density [in press]
Zhang, F.; Heidarifatasmi, H.; Zirwes, T.; Fedoryk, M.; Harth, S.; Sebbar, N.; Habisreuther, P.; Trimis, D.; Bockhorn, H.
2019. 9th European Combustion Meeting (ECM), Lissabon, Portugal, 14 - 17 April 2019

Numerical Simulation of Turbulent Flame Propagation in a Fan-Stirred Combustion Bomb at Elevated Pressures [in press]
Zhang, F.; Zirwes, T.; Habisreuther, P.; Zarzalis, N.; Bockhorn, H.; Trimis, D.
2019. 27th International Colloquium on the Dynamics of Explosions and Reactive Systems, Beijing, China, 8th July - 2nd August 2019

Properties of Z±c(3900) produced in p¯p collisions
D0 Collaboration; Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Aushev, V.; Aushev, Y.; u. a.
2019. Physical review / D, 100 (1), 012005. doi:10.1103/PhysRevD.100.012005

Clustering as Approximation Method to Optimize Hydrological Simulations
Azmi, E.; Ehret, U.; Meyer, J.; Pruijssen, R. van; Streit, A.; Strobl, M.
2019. Euro-Par 2019: Parallel Processing – 25th International Conference on Parallel and Distributed Computing, Göttingen, Germany, August 26–30, 2019, Proceedings. Ed.: R. Yahyapour. Ed.: R. Yahyapour, 256–269, Springer International Publishing. doi:10.1007/978-3-030-29400-7_19

Large-Scale Quasi-DNS of Mixed-Mode Turbulent Combustion [in press]
Zirwes, T.; Zhang, F.; Habisreuther, P.; Bockhorn, H.; Trimis, D.
2019. 90th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), Vienna, Austria, February 18-22, 1019. Ed.: J. Eberhardsteiner, TU Verlag

Ignition behaviour of sulfur in air based on modified reaction kinetics [in press]
Zirwes, T.; Sebbar, N.; Habisreuther, P.; Harth, S.; Zhang, F.; Bockhorn, H.; Trimis, D.
2019. 11th Mediterranean Combustion Symposium (MCS11), Tenerife, Spain, 16-20 June 2019

Identification of evolutionary and kinetic drivers of NAD-dependent signaling
Bockwoldt, M.; Houry, D.; Niere, M.; Gossmann, T. I.; Reinartz, I.; Schug, A.; Ziegler, M.; Heiland, I.
2019. Proceedings of the National Academy of Sciences of the United States of America, 116 (32), 15957–15966. doi:10.1073/pnas.1902346116

Close Nozzle Spray Characteristics of a Prefilming Airblast Atomizer
Holz, S.; Braun, S.; Chaussonnet, G.; Koch, R.; Bauer, H.-J.
2019. Energies, 12 (14), 2835. doi:10.3390/en12142835

Improved Vectorization for Efficient Chemistry Computations in OpenFOAM for Large Scale Combustion Simulations
Zirwes, T.; Zhang, F.; Denev, J. A.; Habisreuther, P.; Bockhorn, H.; Trimis, D.
2019. High Performance Computing in Science and Engineering ’18 - Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2018. Ed.: W. E. Nagel, 209–224, Springer International Publishing

SABCEMM: A Simulator for Agent-Based Computational Economic Market Models
Trimborn, T.; Otte, P.; Cramer, S.; Beikirch, M.; Pabich, E.; Frank, M.
2019. Computational economics. doi:10.1007/s10614-019-09910-1

On the Quality of Wall Time Estimates for Resource Allocation Prediction
Soysal, M.; Berghoff, M.; Klusáček, D.; Streit, A.
2019. ICPP 2019 Proceedings of the 48th International Conference on Parallel Processing: Workshops, Kyoto, Japan — August 05 - 08, 2019, Artikel Nr.: 23 /1–8, Association for Computing Machinery (ACM). doi:10.1145/3339186.3339204

Change in Flame Geometry of an Ethanol Spray Flame by Varying the Spray Characteristics
Galeazzo, F. C. C.; Fukumasu, N. K.; Denev, J. A.; Weis, C.; Habisreuther, P.; Krieger Filho, G. C.
2019. Combustion science and technology, 191 (9), 1693–1710. doi:10.1080/00102202.2019.1639682

Unusual chlorine partitioning in the 2015/16 Arctic winter lowermost stratosphere: Observations and simulations
Johansson, S.; Santee, M. L.; Grooß, J.-U.; Höpfner, M.; Braun, M.; Friedl-Vallon, F.; Khosrawi, F.; Kirner, O.; Kretschmer, E.; Oelhaf, H.; Orphal, J.; Sinnhuber, B.-M.; Tritscher, I.; Ungermann, J.; Walker, K. A.; u. a.
2019. Atmospheric chemistry and physics, 19 (12), 8311–8338. doi:10.5194/acp-19-8311-2019

Theorien von Autorschaft und Stil in Bewegung: Stilistik und Stilometrie in der Romania
Rißler-Pipka, N. (Hrsg.)
2019. Akademische Verlagsgemeinschaft

Einleitung
Rißler-Pipka, N.
2019. Romanische Studien - Beihefte, 6, 5–19

In Search of a New Language: Measuring Style of Góngora and Picasso
Rißler-Pipka, N.
2019. Romanische Studien - Beihefte, 6, 117–149

Tools for Analyzing Parallel I/O
Kunkel, J. M.; Betke, E.; Bryson, M.; Carns, P.; Francis, R.; Frings, W.; Laifer, R.; Mendez, S.
2019. International Conference on High Performance Computing, ISC High Performance 2018; Frankfurt; Germany; 28 June 2018 through 28 June 2018. Ed.: M. Weiland, 49–70, Springer. doi:10.1007/978-3-030-02465-9_4

Rising Up: Hierarchical Metal–Organic Frameworks in Experiments and Simulations
Luo, Y.; Ahmad, M.; Schug, A.; Tsotsalas, M.
2019. Advanced materials, 31 (26), Art.-Nr.: 1901744. doi:10.1002/adma.201901744

Theorien von Autorschaft und Stil in Bewegung : Stilistik und Stilometrie in der Romania [in press]
Rißler-Pipka, N. (Hrsg.)
2019. Akademische Verlagsgemeinschaft

Using On-demand File Systems in HPC Environments
Soysal, M.; Berghoff, M.; Zirwes, T.; Vef, M.-A.; Oeste, S.; Brinkman, A.; Nagel, W. E.; Streit, A.
2019. The 17th Annual Meeting of the 2019 International Conference on High Performance Computing & Simulation (HPCS 2019), Dublin, IR, July 15-19, 2019. doi:10.1109/HPCS48598.2019.9188216

Toward a modular precision ecosystem for high-performance computing
Anzt, H.; Flegar, G.; Grützmacher, T.; Quintana-Ortí, E. S.
2019. The international journal of high performance computing applications, 33 (6), 1069–1078. doi:10.1177/1094342019846547

Labelling OCR Ground Truth for Usage in Repositories
Boenig, M.; Baierer, K.; Hartmann, V.; Federbusch, M.; Neudecker, C.
2019. Proceedings of the 3rd International Conference on Digital Access to Textual Cultural Heritage (DATeCH2019), 3–8, Association for Computing Machinery (ACM). doi:10.1145/3322905.3322916

OCR-D: An end-to-end open source OCR framework for historical printed documents
Neudecker, C.; Baierer, K.; Federbusch, M.; Boenig, M.; Würzner, K.-M.; Hartmann, V.; Herrmann, E.
2019. Proceedings of the 3rd International Conference on Digital Access to Textual Cultural Heritage (DATeCH2019), 53–58, Association for Computing Machinery (ACM). doi:10.1145/3322905.3322917

Machine learning-aided numerical linear Algebra: Convolutional neural networks for the efficient preconditioner generation
Götz, M.; Anzt, H.
2019. Proceedings of ScalA 2018: 9th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, 49–56, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ScalA.2018.00010

High-Performance GPU Implementation of PageRank with Reduced Precision Based on Mantissa Segmentation
Grützmacher, T.; Anzt, H.; Scheidegger, F.; Quintana-Orti, E. S.
2019. Proceedings of IA³ 2018: 8th Workshop on Irregular Applications: Architectures and Algorithms, 61–68, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IA3.2018.00015

Variable-Size Batched Condition Number Calculation on GPUs
Anzt, H.; Dongarra, J.; Flegar, G.; Grützmacher, T.
2019. 2018 30th International Symposium on Computer Architecture and High Performance Computing: SBAC-PAD 2018 ; Lyon, France, 24-27 September 2018 ; Proceedings, 132–139, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CAHPC.2018.8645907

A Jaccard Weights Kernel Leveraging Independent Thread Scheduling on GPUs
Anzt, H.; Dongarra, J.
2019. 2018 30th International Symposium on Computer Architecture and High Performance Computing: SBAC-PAD 2018 ; Lyon, France, 24-27 September 2018 ; Proceedings, 229–232, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CAHPC.2018.8645946

Ein Web Annotation Protocol Server zur Untersuchung vormoderner Wissensbestände
Tonne, D.; Götzelmann, G.; Hegel, P.; Krewet, M.; Hübner, J.; Söring, S.; Löffler, A.; Hitzker, M.; Höfler, M.; Schmidt, T.
2019. DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts. Hrsg.: Patrick Sahle, 283–285, Zenodo

Zeitungen und Zeitschriften als multimodale, digitale Forschungsobjekte: Theorien und Methoden
Rißler-Pipka, N.; Neudecker, C.; Resch, C.; Kampkaspar, D.; Lehmann, J.; Herzgsell, T.
2019. DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts. Hrsg.: P. Sahle, 77–81

L’esthétique numérique de Picasso
Rißler-Pipka, N.
2019. Philologie im Netz, 2019 (16), 39–59

Zwischen Genres und Medien: Formen moderner Prosa in Frankreich = Entre genres et médias: formes de la prose moderne en France
Rißler-Pipka, N.; Schöch, C. (Hrsg.)
2019. Freie Universität Berlin

Rapid interpretation of small-angle X-ray scattering data
Weiel, M.; Reinartz, I.; Schug, A.
2019. PLoS Computational Biology, 15 (3), e1006900. doi:10.1371/journal.pcbi.1006900

Wie sich die Bilder gleichen. Bildähnlichkeitssuche in Drucken des 16. Jahrhunderts
Götzelmann, G.
2019. DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts. Hrsg.: Patrick Sahle, 358–359, Zenodo

Extreme Data Workshop 2018 Forschungszentrum Jülich, 18 – 19 September 2018 Proceedings
Schultz, M.; Pleiter, D.; Bauer, P. (Hrsg.)
2019. Forschungszentrum Jülich

Remote Sensing Data Analytics with the Udocker Container Tool using Multi-GPU Deep Learning Systems
Cavallaro, G.; Kozlov, V.; Götz, M.; Riedel, M.
2019. Proceedings of 2019 Big Data from Space (BiDS’19). Ed.: S. Pierre, 177–180. doi:10.2760/848593

Maximum-principle-satisfying second-order Intrusive Polynomial Moment scheme
Kusch, J.; Alldredge, G. W.; Frank, M.
2019. SMAI Journal of Computational Mathematics, 5, 23–51. doi:10.5802/smai-jcm.42

Procedures for systematic capture and management of analytical data in academia
Potthoff, J.; Tremouilhac, P.; Hodapp, P.; Neumair, B.; Bräse, S.; Jung, N.
2019. Analytica Chimica Acta: X, 1, Article: 100007. doi:10.1016/j.acax.2019.100007

Ray effect mitigation for the discrete ordinates method through quadrature rotation
Camminady, T.; Frank, M.; Küpper, K.; Kusch, J.
2019. Journal of computational physics, 382, 105–123. doi:10.1016/j.jcp.2019.01.016

On Using Clustering for the Optimization of Hydrological Simulations
Azmi, E.
2019. IEEE International Conference on Data Mining Workshops(ICDMW), Singapore, November 17 - 20 2018, 1495–1496, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICDMW.2018.00215

A unified comparative study of heuristic algorithms for double combinatorial auctions: Locality-constrained resource allocation problems
Gudu, D.; Hardt, M.; Streit, A.
2019. Agents and Artificial Intelligence: 10th International Conference, ICAART 2018, Funchal, Madeira, Portugal, January 16-18,2018. Revised Selected Papers., 3–22. doi:10.1007/978-3-030-05453-3_1

Automatic Layout Analysis and Visual Exploration of Multidimensional Datasets with Applications in the Digital Humanities. Dissertation
Chandna, S.
2019. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000089239

The GridKa Tape System: status and outlook
Ressmann, D.; Lobontu, D.; Beitzinger, M.; Schäfer, K.; Heiss, A.; Petzold, A.; Musheghyan, H.
2019. The European physical journal / Web of Conferences, 214, Art. Nr.: 04029. doi:10.1051/epjconf/201921404029

Concept and Analysis of Information Spaces to improve Prediction-Based Compression
Cayoglu, U.; Tristram, F.; Meyer, J.; Kerzenmacher, T.; Braesicke, P.; Streit, A.
2019. 2018 IEEE International Conference on Big Data (Big Data), Seattle, WA, December 10 - 13, 2018. Ed.: Y. Song, 3392–3401, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData.2018.8622313

Ignition of combustible mixtures by hot particles at varying relative speeds
Zirwes, T.; Zhang, F.; Häber, T.; Bockhorn, H.
2019. Combustion science and technology, 191 (1), 178–195. doi:10.1080/00102202.2018.1435530

Studying the occurrence and burnt area of wildfires using zero-one-inflated structured additive beta regression
Ríos-Pena, L.; Kneib, T.; Cadarso-Suárez, C.; Klein, N.; Marey-Pérez, M.
2018. Environmental Modelling & Software, 110, 107–118. doi:10.1016/j.envsoft.2018.03.008

Feasibility and robustness of dynamic 18F-FET PET based tracer kinetic models applied to patients with recurrent high-grade glioma prior to carbon ion irradiation
Debus, C.; Afshar-Oromieh, A.; Floca, R.; Ingrisch, M.; Knoll, M.; Debus, J.; Haberkorn, U.; Abdollahi, A.
2018. Scientific Reports, 8 (1), Artkl.Nr.: 14760. doi:10.1038/s41598-018-33034-5

Impact of 18F-FET PET on Target Volume Definition and Tumor Progression of Recurrent High Grade Glioma Treated with Carbon-Ion Radiotherapy
Debus, C.; Waltenberger, M.; Floca, R.; Afshar-Oromieh, A.; Bougatf, N.; Adeberg, S.; Heiland, S.; Bendszus, M.; Wick, W.; Rieken, S.; Haberkorn, U.; Debus, J.; Knoll, M.; Abdollahi, A.
2018. Scientific Reports, 8 (1), Artkl.Nr.: 7201. doi:10.1038/s41598-018-25350-7

On approximative linear Boltzmann transport equation for charged particles
Tervo, J.; Kokkonen, P.; Frank, M.; Herty, M.
2018. Mathematical models and methods in applied sciences (M 3 AS), 28 (14), 2905–2939. doi:10.1142/S0218202518500641

Stratospheric ozone loss over the Eurasian continent induced by the polar vortex shift
Zhang, J.; Tian, W.; Xie, F.; Chipperfield, M. P.; Feng, W.; Son, S.-W.; Abraham, N. L.; Archibald, A. T.; Bekki, S.; Butchart, N.; Deushi, M.; Dhomse, S.; Han, Y.; Jöckel, P.; Kinnison, D.; u. a.
2018. Nature Communications, 9 (1), 206. doi:10.1038/s41467-017-02565-2

A comparative study of limiting strategies in discontinuous Galerkin schemes for the model of radiation transport
Chidyagwai, P.; Frank, M.; Schneider, F.; Seibold, B.
2018. Journal of computational and applied mathematics, 342, 399–418. doi:10.1016/j.cam.2018.04.017

More green space is related to less antidepressant prescription rates in the Netherlands: A Bayesian geoadditive quantile regression approach
Helbich, M.; Klein, N.; Roberts, H.; Hagedoorn, P.; Groenewegen, P. P.
2018. Environmental Research, 166, 290–297. doi:10.1016/j.envres.2018.06.010

Quantifying river incision into low-relief surfaces using local and catchment-wide 10Be denudation rates
Wolff, R.; Hetzel, R.; Strobl, M.
2018. Earth surface processes and landforms, 43 (11), 2327–2341. doi:10.1002/esp.4394

Formation of a Secretion-Competent Protein Complex by a Dynamic Wrap-around Binding Mechanism
Gupta, A. A.; Reinartz, I.; Karunanithy, G.; Spilotros, A.; Jonna, V. R.; Hofer, A.; Svergun, D. I.; Baldwin, A. J.; Schug, A.; Wolf-Watz, M.
2018. Journal of molecular biology, 430 (18), 3157–3169. doi:10.1016/j.jmb.2018.07.014

Bayesian Multivariate Distributional Regression With Skewed Responses and Skewed Random Effects
Michaelis, P.; Klein, N.; Kneib, T.
2018. Journal of Computational and Graphical Statistics, 27 (3), 602–611. doi:10.1080/10618600.2017.1395343

Perturbation-based inference for diffusion processes: Obtaining effective models from multiscale data
Krumscheid, S.
2018. Mathematical Models and Methods in Applied Sciences, 28 (08), 1565–1597. doi:10.1142/S0218202518500434

A new high-order fluid solver for tokamak edge plasma transport simulations based on a magnetic-field independent discretization
Giorgiani, G.; Camminady, T.; Bufferand, H.; Ciraolo, G.; Ghendrih, P.; Guillard, H.; Heumann, H.; Nkonga, B.; Schwander, F.; Serre, E.; Tamain, P.
2018. Contributions to plasma physics, 58 (6-8), 688–695. doi:10.1002/ctpp.201700172

Best-effort inductive logic programming via fine-grained cost-based hypothesis generation. The inspire system at the inductive logic programming competition
Schüller, P.; Benz, M.
2018. Machine learning, 107 (7), 1141–1169. doi:10.1007/s10994-018-5708-2

Sandboxing of biomedical applications in Linux containers based on system call evaluation
Witt, M.; Jansen, C.; Krefting, D.; Streit, A.
2018. Concurrency and computation, 30 (12), e4484. doi:10.1002/cpe.4484

Quasi-steady state reduction for the Michaelis–Menten reaction–diffusion system
Frank, M.; Lax, C.; Walcher, S.; Wittich, O.
2018. Journal of mathematical chemistry, 56 (6), 1759–1781. doi:10.1007/s10910-018-0891-8

Using Jacobi iterations and blocking for solving sparse triangular systems in incomplete factorization preconditioning
Chow, E.; Anzt, H.; Scott, J.; Dongarra, J.
2018. Journal of parallel and distributed computing, 119, 219–230. doi:10.1016/j.jpdc.2018.04.017

On existence of solutions for Boltzmann Continuous Slowing Down transport equation
Tervo, J.; Kokkonen, P.; Frank, M.; Herty, M.
2018. Journal of mathematical analysis and applications, 460 (1), 271–301. doi:10.1016/j.jmaa.2017.11.052

Crystal-melt interface mobility in bcc Fe: Linking molecular dynamics to phase-field and phase-field crystal modeling
Guerdane, M.; Berghoff, M.
2018. Physical review / B, 97 (14), 144105. doi:10.1103/PhysRevB.97.144105

Simulation of FRET dyes allows quantitative comparison against experimental data
Reinartz, I.; Sinner, C.; Nettels, D.; Stucki-Buchli, B.; Stockmar, F.; Panek, P. T.; Jacob, C. R.; Nienhaus, G. U.; Schuler, B.; Schug, A.
2018. The journal of chemical physics, 148 (12), 123321. doi:10.1063/1.5010434

Optimization and performance evaluation of the IDR iterative Krylov solver on GPUs
Anzt, H.; Kreutzer, M.; Ponce, E.; Peterson, G. D.; Wellein, G.; Dongarra, J.
2018. The international journal of high performance computing applications, 32 (2), 220–230. doi:10.1177/1094342016646844

Intrusive methods in uncertainty quantification and their connection to kinetic theory
Kusch, J.; Frank, M.
2018. International journal of advances in engineering sciences and applied mathematics, 10 (1), 54–69. doi:10.1007/s12572-018-0211-3

A spectral Galerkin method for the fractional order diffusion and wave equation
Camminady, T.; Frank, M.
2018. International journal of advances in engineering sciences and applied mathematics, 10 (1), 90–104. doi:10.1007/s12572-018-0208-y

P-PIF: a ProvONE provenance interoperability framework for analyzing heterogeneous workflow specifications and provenance traces
Prabhune, A.; Zweig, A.; Stotzka, R.; Hesser, J.; Gertz, M.
2018. Distributed and parallel databases, 36 (1), 219–264. doi:10.1007/s10619-017-7216-y

A non-noble Cr–Ni-based catalyst for the oxygen reduction reaction in alkaline polymer electrolyte fuel cells
Faubert, P.; Kondov, I.; Qazzazie, D.; Yurchenko, O.; Müller, C.
2018. MRS communications, 8 (01), 160–167. doi:10.1557/mrc.2018.13

SSAGES : Software Suite for Advanced General Ensemble Simulations
Sidky, H.; Colón, Y. J.; Helfferich, J.; Sikora, B. J.; Bezik, C.; Chu, W.; Giberti, F.; Guo, A. Z.; Jiang, X.; Lequieu, J.; Li, J.; Moller, J.; Quevillon, M. J.; Rahimi, M.; Ramezani-Dakhel, H.; u. a.
2018. The journal of chemical physics, 148 (4), Art.Nr. 044104. doi:10.1063/1.5008853

Effect Selection in Distributional Regression
Klein, N.; Carlan, M.; Kneib, T.; Lang, S.; Wagner, H.
2018. Proceedings of the 33th International Workshop on Statistical Modelling. Vol. 1, 157–162, Statistical Modelling Society

Quality and resource efficiency in hospital service provision: A geoadditive stochastic frontier analysis of stroke quality of care in Germany
Pross, C.; Strumann, C.; Geissler, A.; Herwartz, H.; Klein, N.
2018. (A. Arrieta, Hrsg.) PLOS ONE, 13 (9), e0203017. doi:10.1371/journal.pone.0203017

Multilevel Monte Carlo Approximation of Functions
Krumscheid, S.; Nobile, F.
2018. SIAM/ASA Journal on Uncertainty Quantification, 6 (3), 1256–1293. doi:10.1137/17M1135566

Operational experience and commissioning of the Belle II vertex detector
Schwenker, B.; Abudinén, F.; Ackermann, K.; Ahlburg, P.; Aihara, H.; Albalawi, M.; Alonso, O.; Andricek, L.; Ayad, R.; Aziz, T.; Babu, V.; Bacher, S.; Bahinipati, S.; Bai, Y.; Barberio, E.; u. a.
2018. Collaborations, SVD (Hrsg.), 27th International Workshop on Vertex Detectors (VERTEX 2018), Chennai, IND, October 22-28, 2018, Scuola Internazionale Superiore di Studi Avanzati (SISSA)

La prima infrastruttura di data management per le nanoscienze
Aversa, R.; Cozzini, S.
2018. Conferenza GARR 2018 - Data (R)evolution - Selected Papers, Cagliari, Italy, 3-5 ottobre 2018, 26–29, Consortium GARR. doi:10.26314/GARR-Conf18-proceedings-04

Batch Job Scheduling Using Enhanced Walltime Prediction
Klusáček, D.; Soysal, M.
2018. CGW Workshop ’18 (CGW’18), Kraków, PL, 22-24 October 2018, AGH

Komplexe Modellierung: Trump gegen die Wissenschaft – Gibt es den Klimawandel wirklich?
Hattebuhr, M.; Frank, M.; Roeckerath, C.
2018. Beiträge zum Mathematikunterricht 2018. Bd.4, 731–734, WTM Verlag für wissenschaftliche Texte und Medien

Komplexe Modellierung: Wie funktionieren eigentlich Animationsfilme und was hat das mit Mathe zu tun?
Wohak, K.; Frank, M.; Roeckerath, C.
2018. Beiträge zum Mathematikunterricht 2018. Bd.4, 2023–2026, WTM Verlag für wissenschaftliche Texte und Medien

Efficient ray-tracing with real weather data
Richter, P.; Tinnes, J.; Schwarzbözl, P.; Rong, A.; Frank, M.
2018. SolarPACES 2017 : International Conference on Concentrating Solar Power and Chemical Energy Systems. Ed.: R. Mancilla, 210014, American Institute of Physics (AIP). doi:10.1063/1.5067216

SunFlower: A new solar tower simulation method for use in field layout optimization
Richter, P.; Heiming, G.; Lukas, N.; Frank, M.
2018. SolarPACES 2017 : International Conference on Concentrating Solar Power and Chemical Energy Systems. Ed.: R. Mancilla, 210015, American Institute of Physics (AIP). doi:10.1063/1.5067217

Towards reduction of computational cost for large-scale combustion modelling with a multi-regional concept
Zhang, F.; Zirwes, T.; Habisreuther, P.; Bockhorn, H.
2018. Progress in computational fluid dynamics, 18 (6), 333–346. doi:10.1504/PCFD.2018.096616

The Helmholtz Analytics Toolkit (HEAT): A scientific Big Data Library for HPC
Krajsek, K.; Comito, C.; Götz, M.; Hagemeier, B.; Knechtges, P.; Siggel, M.
2018. Proceedings of the Extreme Data Workshop 2018

OIDC-Agent: Managing OpenID Connect Tokens on the Command Line
Zachmann, G.
2018. Lecture Notes in Informatics (LNI) - Seminars 14, 11–21

Grab, Grabmal
Götzelmann, G.
2018. Literarische Orte in deutschsprachigen Erzählungen des Mittelalters – Ein Handbuch. Ed.: T. Renz, 199–208, De Gruyter

A Modular Software Framework for Compression of Structured Climate Data
Cayoglu, U.; Schröter, J.; Meyer, J.; Streit, A.; Braesicke, P.
2018. Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2018, Seattle, WA, November 06-09, 2018, 556–559, Association for Computing Machinery (ACM). doi:10.1145/3274895.3274897

Mastering Opportunistic Computing Resources for HEP
Schnepf, M. J.; Heidecker, C.; Fischer, M.; Giffels, M.; Kuehn, E.; Heiss, A.; Petzold, A.; Quast, G.
2018. Journal of physics / Conference Series, 1085 (3), Art. Nr.: 032056. doi:10.1088/1742-6596/1085/3/032056

Provisioning of data locality for HEP analysis workflows
Heidecker, C.; Schnepf, M. J.; Kuehn, E.; Fischer, M.; Giffels, M.; Quast, G.
2018. Journal of physics / Conference Series, 1085 (3), Art. Nr.: 032005. doi:10.1088/1742-6596/1085/3/032005

Non-Collective Scalable Global Network Based on Local Communications
Berghoff, M.; Kondov, I.
2018. 9th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA), Dallas, TX, USA, November 12, 2018, 25–32, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ScalA.2018.00007

Case study of ozone anomalies over northern Russia in the 2015/2016 winter: measurements and numerical modelling
Timofeyev, Y. M.; Smyshlyaev, S. P.; Virolainen, Y. A.; Garkusha, A. S.; Polyakov, A. V.; Motsakov, M. A.; Kirner, O.
2018. Annales geophysicae, 36 (6), 1495–1505. doi:10.5194/angeo-36-1495-2018

Evidence for Zc±(3900) in semi-inclusive decays of b-flavored hadrons
D0 Collaboration; Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Aushev, V.; Aushev, Y.; u. a.
2018. Physical review / D, 98 (5), 052010–1. doi:10.1103/PhysRevD.98.052010

Optimized Chemistry and Detailed Transport for Massively Parallel Simulations of Turbulent Combustion with OpenFOAM
Zirwes, T.; Zhang, F.; Denev, J. A.; Habisreuther, P.; Bockhorn, H.; Trimis, D.
2018. The 13th OpenFOAM Workshop (OFW13), Shanghai, China, June 24-29 2018. Ed.: J. Wang

Investigation of S2 + Air Combustion
Sebbar, N.; Zirwes, T.; Habisreuther, P.; Bockhorn, H.; Trimis, D.
2018. Proceedings of Joint Meeting of the German and Italian Sections of the Combustion Institute, Sorrento, Italy, May 23-26, 2018. Ed.: H. Bockhorn, VI10, Associazione Sezione Italiana del Combustion Institute (ASICI)

ICON-ART 2.1: a flexible tracer framework and its application for composition studies in numerical weather forecasting and climate simulations
Schröter, J.; Rieger, D.; Stassen, C.; Vogel, H.; Weimer, M.; Werchner, S.; Förstner, J.; Prill, F.; Reinert, D.; Zängl, G.; Giorgetta, M.; Ruhnke, R.; Vogel, B.; Braesicke, P.
2018. Geoscientific model development, 11 (10), 4043–4068. doi:10.5194/gmd-11-4043-2018

Revisiting the Mystery of Recent Stratospheric Temperature Trends
Maycock, A. C.; Randel, W. J.; Steiner, A. K.; Karpechko, A. Y.; Christy, J.; Saunders, R.; Thompson, D. W. J.; Zou, C.-Z.; Chrysanthou, A.; Luke Abraham, N.; Akiyoshi, H.; Archibald, A. T.; Butchart, N.; Chipperfield, M.; Dameris, M.; u. a.
2018. Geophysical research letters. doi:10.1029/2018GL078035

Die Digitalisierung des goldenen Zeitalters – Editionsproblematik und stilometrische Autorschaftsattribution am Beispiel des Quijote
Rißler-Pipka, N.
2018. Zeitschrift für digitale Geisteswissenschaften, 4 (3). doi:10.17175/2018_004

Evaluation of MUSICA IASI tropospheric water vapour profiles using theoretical error assessments and comparisons to GRUAN Vaisala RS92 measurements
Borger, C.; Schneider, M.; Ertl, B.; Hase, F.; García, O. E.; Sommer, M.; Höpfner, M.; Tjemkes, S. A.; Calbet, X.
2018. Atmospheric measurement techniques, 11 (9), 4981–5006. doi:10.5194/amt-11-4981-2018

Juan Gris: Retrato de Picasso (1912)
Rißler-Pipka, N.
2018. Meisterwerke der spanischen Malerei in Einzeldarstellungen. Hrsg.: R. Junkerjürgen, 309–322, Erich Schmidt Verlag GmbH & Co. KG (ESV)

Combinatorial Auction Algorithm Selection for Cloud Resource Allocation Using Machine Learning
Gudu, D.; Hardt, M.; Streit, A.
2018. Euro-Par 2018: Parallel Processing. Proceedings ot the 24th International Conference on Parallel and Distributed Computing, Turin, I, August 27 - 31, 2018, Ed.: M. Aldinucci, 378–391, Springer International Publishing. doi:10.1007/978-3-319-96983-1_27

Optimizing Load Balancing of Reacting Flow Solvers in OpenFOAM for High Performance Computing
Zirwes, T.; Zhang, F.; Habisreuther, P.; Denev, J. A.; Bockhorn, H.; Trimis, D.
2018. 6th ESI OpenFOAM User Conference 2018, Hamburg, 23.-25. Oktober 2018, 1–13, ESI Group

Analysis of Job Metadata for Enhanced Wall Time Prediction
Soysal, M.; Berghoff, M.; Streit, A.
2018. Job Scheduling Strategies for Parallel Processing : 22nd International Workshop, JSSPP 2018, Vancouver, BC, Canada, May 25, 2018, Revised Selected Papers. Ed.: Dalibor Klusáček, 14 S., Springer. doi:10.1007/978-3-030-10632-4_1

Change in flame geometry of an ethanol spray flame by varying the injection frequency
Galeazzo, F. C. C.; Fukumasu, N. K.; Denev, J. A.; Krieger Filho, G. C.
2018. Joint Meeting German and Italian Sections of the Combustion Institute, 41st Meeting of the Italian Section of The Combustion Institute, Sorrento, I, May 23-26, 2018. Proceedings. Ed.: H. Bockhorn, Article VIII2, ASICI

Detailed Transport and Performance Optimization for Massively Parallel Simulations of Turbulent Combustion with OpenFOAM
Zirwes, T.; Zhang, F.; Denev, J. A.; Habisreuther, P.; Bockhorn, H.; Trimis, D.
2018. The 13th OpenFOAM Workshop (OFW13), Shanghai, China, June 24-29, 2018. Ed.: J. Wang, 142–145, CMHL

Spectral response of different combustion models in LES of direct combustion noise
Zhang, F.; Zirwes, T.; Nawroth, H.; Li, N.; Habisreuther, P.; Bockhorn, H.; Trimis, D.; Paschereit, C. O.
2018. Joint Meeting German and Italian Sections of the Combustion Institute, 41st Meeting of the Italian Section of The Combustion Institute, Sorrento, I, May 23-26, 2018. Proceedings. Ed.: H. Bockhorn, Article I8, ASICI

Large Eddy Simulation of Turbulent Flow in a Fan-stirred Combustion Vessel
Zhang, F.; Zirwes, T.; Habisreuther, P.; Zarzalis, N.; Trimis, D.; Bockhorn, H.
2018. Joint Meeting German and Italian Sections of the Combustion Institute, 41st Meeting of the Italian Section of The Combustion Institute, Sorrento, I, May 23-26, 2018. Proceedings. Ed.: H. Bockhorn, Article I10, ASICI

Investigation of S₂ + Air combustion
Sebbar, N.; Zirwes, T.; Habisreuther, P.; Bockhorn, H.; Trimis, D.
2018. Joint Meeting German and Italian Sections of the Combustion Institute, 41st Meeting of the Italian Section of The Combustion Institute, Sorrento, I, May 23-26, 2018. Proceedings. Ed.: H. Bockhorn, Article VI10, ASICI

S₂ + Air Combustion: Reaction Kinetics, Flame Structure, and Laminar Flame Behavior
Sebbar, N.; Zirwes, T.; Habisreuther, P.; Bozzelli, J. W.; Bockhorn, H.; Trimis, D.
2018. Energy & fuels, 32 (10), 10184–10193. doi:10.1021/acs.energyfuels.8b01019

Wnt/PCP controls spreading of Wnt/β-catenin signals by cytonemes in vertebrates
Mattes, B.; Dang, Y.; Greicius, G.; Kaufmann, L. T.; Prunsche, B.; Rosenbauer, J.; Stegmaier, J.; Mikut, R.; Özbek, S.; Nienhaus, G. U.; Schug, A.; Virshup, D. M.; Scholpp, S.
2018. eLife, 7, Article No. e36953. doi:10.7554/eLife.36953

The representation of solar cycle signals in stratospheric ozone – Part 2: Analysis of global models
Maycock, A. C.; Matthes, K.; Tegtmeier, S.; Schmidt, H.; Thiéblemont, R.; Hood, L.; Akiyoshi, H.; Bekki, S.; Deushi, M.; Jöckel, P.; Kirner, O.; Kunze, M.; Marchand, M.; Marsh, D. R.; Michou, M.; u. a.
2018. Atmospheric chemistry and physics, 18 (15), 11323–11343. doi:10.5194/acp-18-11323-2018

INDIGO-DataCloud: a Platform to Facilitate Seamless Access to E-Infrastructures
Salomoni, D.; Campos, I.; Gaido, L.; Lucas, J. M. de; Solagna, P.; Gomes, J.; Matyska, L.; Fuhrman, P.; Hardt, M.; Donvito, G.; Dutka, L.; Plociennik, M.; Barbera, R.; Blanquer, I.; Ceccanti, A.; u. a.
2018. Journal of grid computing. doi:10.1007/s10723-018-9453-3

Fractional diffusion limits of non-classical transport equations
Frank, M.; Sun, W.
2018. Kinetic and related models, 11 (6), 1503–1526. doi:10.3934/krm.2018059

ParILUT---A New Parallel Threshold ILU Factorization
Anzt, H.; Chow, E.; Dongarra, J.
2018. SIAM journal on scientific computing, 40 (4), C503–C519. doi:10.1137/16M1079506

Comparison of ECHAM5/MESSy Atmospheric Chemistry (EMAC) simulations of the Arctic winter 2009/2010 and 2010/2011 with Envisat/MIPAS and Aura/MLS observations
Khosrawi, F.; Kirner, O.; Stiller, G.; Höpfner, M.; Santee, M. L.; Kellmann, S.; Braesicke, P.
2018. Atmospheric chemistry and physics, 18 (12), 8873–8892. doi:10.5194/acp-18-8873-2018

Estimates of ozone return dates from Chemistry-Climate Model Initiative simulations
Dhomse, S. S.; Kinnison, D.; Chipperfield, M. P.; Salawitch, R. J.; Cionni, I.; Hegglin, M. I.; Abraham, N. L.; Akiyoshi, H.; Archibald, A. T.; Bednarz, E. M.; Bekki, S.; Braesicke, P.; Butchart, N.; Dameris, M.; Deushi, M.; u. a.
2018. Atmospheric chemistry and physics, 18 (11), 8409–8438. doi:10.5194/acp-18-8409-2018

Approximate algorithms for double combinatorial auctions for resource allocation in clouds: An empirical comparison
Gudu, D. M.; Zachmann, G.; Hardt, M.; Streit, A.
2018. 10th International Conference on Agents and Artificial Intelligence, ICAART 2018; Funchal, Madeira; Portugal; 16 January 2018 through 18 January 2018. Ed.: J. van den Herik, 58–69, SciTePress. doi:10.5220/0006593900580069

Online Analysis of Dynamic Streaming Data. Dissertation
Kühn, E.
2018. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000083227

Validation of Atmospheric Numerical Models Based on Satellite Measurements of Ozone Columns
Virolainen, Y. A.; Timofeev, Y. M.; Berezin, I. A.; Smyshlyaev, S. P.; Motsakov, M. A.; Kirner, O.
2018. Russian meteorology and hydrology, 43 (3), 161–167. doi:10.3103/S1068373918030044

Mean field limit of a behavioral financial market model
Trimborn, T.; Frank, M.; Martin, S.
2018. Physica / A, 505, 613–631. doi:10.1016/j.physa.2018.03.079

Massively Parallel Stencil Code Solver with Autonomous Adaptive Block Distribution
Berghoff, M.; Kondov, I.; Hötzer, J.
2018. IEEE transactions on parallel and distributed systems, 29 (10), 2282–2296. doi:10.1109/TPDS.2018.2819672

Ozone Temporal Variability in the Subarctic Region: Comparison of Satellite Measurements with Numerical Simulations
Shved, G. M.; Virolainen, Y. A.; Timofeyev, Y. M.; Ermolenko, S. I.; Smyshlyaev, S. P.; Motsakov, M. A.; Kirner, O.
2018. Izvestiya / Atmospheric and oceanic physics, 54 (1), 32–38. doi:10.1134/S0001433817060111

Variable-size batched Gauss–Jordan elimination for block-Jacobi preconditioning on graphics processors
Anzt, H.; Dongarra, J.; Flegar, G.; Quintana-Ortí, E. S.
2018. Parallel computing, 81, 131–146. doi:10.1016/j.parco.2017.12.006

An Adaptive Index Recommendation System (AIRs) on Document-Based Databases. Dissertation
Ameri, P.
2018. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000078779

Incomplete Sparse Approximate Inverses for Parallel Preconditioning
Anzt, H.; Huckle, T. K.; Bräckle, J.; Dongarra, J.
2018. Parallel computing, 71, 1–22. doi:10.1016/j.parco.2017.10.003

Automated Code Generation for Maximizing Performance of Detailed Chemistry Calculations in OpenFOAM
Zirwes, T.; Zhang, F.; Denev, J. A.; Habisreuther, P.; Bockhorn, H.
2018. High Performance Computing in Science and Engineering ’ 17 - Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2017. Ed.: W. Nagel, 189–204, Springer-Verlag. doi:10.1007/978-3-319-68394-2_11

OpenGL® API Based Analysis of Large Datasets in a Cloud Environment
Mexner, W.; Bonn, M.; Kopmann, A.; Mauch, V.; Ressmann, D.; Chilingaryan, S.; Tan Jerome, N.; Kamp, T. Van de; Heuveline, V.; Lösel, P.; Schmelzle, S.; Heethoff, M.
2018. Design and Use of Virtualization Technology in Cloud Computing. Ed.: P. Kumar Das, 161–181, IGI Global. doi:10.4018/978-1-5225-2785-5.ch006

E-Science-Tage 2017: Forschungsdaten managen
Kratzke, J.; Heuveline, V. (Hrsg.)
2017. Heidelberger E-Books (heiBOOKS). doi:10.11588/heibooks.285.377

Study of Ozone Layer Variability near St. Petersburg on the Basis of SBUV Satellite Measurements and Numerical Simulation (2000–2014)
Virolainen, Y. A.; Timofeyev, Y. M.; Smyshlyaev, S. P.; Motsakov, M. A.; Kirner, O.
2017. Izvestiya / Atmospheric and oceanic physics, 53 (9), 911–917. doi:10.1134/S0001433817090328

Editorial “Joint modeling of longitudinal and time‐to‐event data and beyond”
Cadarso Suárez, C.; Klein, N.; Kneib, T.; Molenberghs, G.; Rizopoulos, D.
2017. Biometrical Journal, 59 (6), 1101–1103. doi:10.1002/bimj.201700180

Studying the relationship between a woman’s reproductive lifespan and age at menarche using a Bayesian multivariate structured additive distributional regression model
Duarte, E.; Sousa, B. de; Cadarso-Suárez, C.; Klein, N.; Kneib, T.; Rodrigues, V.
2017. Biometrical Journal, 59 (6), 1232–1246. doi:10.1002/bimj.201600245

Boosting joint models for longitudinal and time‐to‐event data
Waldmann, E.; Taylor-Robinson, D.; Klein, N.; Kneib, T.; Pressler, T.; Schmid, M.; Mayr, A.
2017. Biometrical Journal, 59 (6), 1104–1121. doi:10.1002/bimj.201600158

Integrating multivariate conditionally autoregressive spatial priors into recursive bivariate models for analyzing environmental sensitivity of mussels
Thaden, H.; Pata, M. P.; Klein, N.; Cadarso-Suárez, C.; Kneib, T.
2017. Spatial Statistics, 22 (SI, 2), 419–433. doi:10.1016/j.spasta.2017.07.005

Denitrification, dehydration and ozone loss during the 2015/2016 Arctic winter
Khosrawi, F.; Kirner, O.; Sinnhuber, B.-M.; Johansson, S.; Höpfner, M.; Santee, M. L.; Froidevaux, L.; Ungermann, J.; Ruhnke, R.; Woiwode, W.; Oelhaf, H.; Braesicke, P.
2017. Atmospheric chemistry and physics, 17 (21), 12893–12910. doi:10.5194/acp-17-12893-2017

Preconditioned Krylov solvers on GPUs
Anzt, H.; Gates, M.; Dongarra, J.; Kreutzer, M.; Wellein, G.; Köhler, M.
2017. Parallel computing, 68 (October), 32–44. doi:10.1016/j.parco.2017.05.006

Opportunistic data locality for end user data analysis
Fischer, M.; Heidecker, C.; Kuehn, E.; Quast, G.; Giffels, M.; Schnepf, M.; Heiss, A.; Petzold, A.
2017. Journal of physics / Conference Series, 898 (Track 3), 052034. doi:10.1088/1742-6596/898/5/052034

The machine/job features mechanism
Alef, M.; Cass, T.; Keijser, J. J.; McNab, A.; Roiser, S.; Schwickerath, U.; Sfiligoi, I.
2017. Journal of physics / Conference Series, 898, Art.Nr. 092032. doi:10.1088/1742-6596/898/9/092032

Advancing data management and analysis in different scientific disciplines
Fischer, M.; Gasthuber, M.; Giesler, A.; Hardt, M.; Meyer, J.; Prabhune, A.; Rigoll, F.; Schwarz, K.; Streit, A.
2017. Journal of physics / Conference Series, 898 (8), Art.Nr. 082026. doi:10.1088/1742-6596/898/8/082026

Adaptive Lossy Compression of Complex Environmental Indices Using Seasonal Auto-Regressive Integrated Moving Average Models
Cayoglu, U.; Braesicke, P.; Kerzenmacher, T.; Meyer, J.; Streit, A.
2017. IEEE 13th International Conference on e-Science (e-Science), Auckland, NZ, October, 24-27, 2017, 315–324, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/eScience.2017.45

V-FOR-WaTer - Virtuelle Forschungsumgebung für die Wasser- und terrestrische Umweltforschung
Azmi, E.; Hassler, S.; Mälicke, M.; Meyer, J.; Strobl, M.; Zehe, E.
2017. E-Science-Tage 2017: Forschungsdaten managen. Heidelberg University, Universtitätsbibliothek Heidelberg. doi:10.11588/heidok.00022889

Bayesian Joint Modelling of Distributional Regression
Waldmann, E.; Klein, N.; Taylor-Robinson, D.
2017. Proceedings of the 32th International Workshop on Statistical Modelling. Ed.: M. Grzegorczyk. Vol. 1, 305–310, Statistical Modelling Society

Boosting distributional regression models for multivariate responses
Mayr, A.; Thomas, J.; Schmid, M.; Faschingbauer, F.; Klein, N.
2017. Proceedings of the 32th International Workshop on Statistical Modelling. Ed.: M. Grzegorczyk. Vol. 1, 97–102, Statistical Modelling Society

Structured additive distributional regression for analysing landings per unit effort in fisheries research
Mamouridis, V.; Klein, N.; Kneib, T.; Cadarso Suarez, C.; Maynou, F.
2017. Mathematical Biosciences, 283, 145–154. doi:10.1016/j.mbs.2016.11.016

Impact of fitting algorithms on errors of parameter estimates in dynamic contrast-enhanced MRI
Debus, C.; Floca, R.; Nörenberg, D.; Abdollahi, A.; Ingrisch, M.
2017. Physics in Medicine & Biology, 62 (24), 9322–9340. doi:10.1088/1361-6560/aa8989

A point kernel algorithm for microbeam radiation therapy
Debus, C.; Oelfke, U.; Bartzsch, S.
2017. Physics in Medicine & Biology, 62 (21), 8341–8359. doi:10.1088/1361-6560/aa8d63

Nonclassical particle transport in heterogeneous materials
Camminady, T.; Frank, M.; Larsen, E. W.
2017. M&C 2017 : International Conference on Mathematics & Computational Methods Applied to Nuclear Science & Engineering. USB

AARC: First draft of the Blueprint Architecture for Authentication and Authorisation Infrastructures
Biancini, A.; Florio, L.; Haase, M.; Hardt, M.; Jankowski, M.; Jensen, J.; Kanellopoulos, C.; Liampotis, N.; Licehammer, S.; Memon, S.; Dijk, N. van; Paetow, S.; Prochazka, M.; Sallé, M.; Solagna, P.; u. a.
2017. arXiv [cs.CR] : Cryptography and Security, arXiv.1611.07832

Automatic Documentation of the Development of Numerical Models for Scientific Applications using Specific Revision Control
Zinner, M.; Rink, K.; Jäkel, R.; Feldhoff, K.; Grunzke, R.; Fischer, T.; Song, R.; Walther, M.; Jejkal, T.; Kolditz, O.; Nagel, W. E.
2017. Twelfth International Conference on Software Engineering Advances (ICSEA 2017), Athen, GR, October 8-12, 2017. Ed.: L. Lavazza, International Academy

Einfluss von erhöhtem Druck auf die Änderung der 549 Flammendynamik durch Streckung in vorgemischten Flammen
Zirwes, T.; Zhang, F.; Denev, J. A.; Habisreuther, P.; Bockhorn, H.; Zarzalis, N.
2017. Verbrennung und Feuerung : 28. Deutscher Flammentag 2017, Darmstadt, Germany, 6th - 7th September 2017, 549–562, VDI Verlag

Direct numerical simulation of ignition by hot moving particles
Zirwes, T.; Zhang, F.; Häber, T.; Roth, D.; Bockhorn, H.
2017. 26th International Colloquium on the Dynamics of Explosions and Reactive System (ICDERS), Boston, MA, July 30 - August 4, 2017. Papers publ.online

Response of Local and Global Consumption Speed to Stretch in Laminar Steady-State Flames
Zirwes, T.; Zhang, F.; Denev, J. A.; Habisreuther, P.; Bockhorn, H.; Zarzalis, N.
2017. Proceedings of the 8th European Combustion Meeting, Dubrovnik, HR, April 18-21, 2017. Ed.: N. Duic

Coordinating Operational Security in evolving distributed IT-Infrastructures
Brillault, V.; Cornwall, L.; Dias, N.; Dussa, T.; Ferry, S.; Gabriel, S.; Groep, D.; Kelsey, D.; Kouril, D.; Krasovec, B.; Neilson, I.; Yarochkin, F.
2017. Global Challenges - From Open Data to Open Science : Proceedings of the International Symposium on Grids & Clouds 2017, ISGC 2017, Taipei, Taiwan, 5th - 10th March 2017

Local quasi-Monte Carlo exploration
Tessari, L.; Hanika, J.; Dachsbacher, C.
2017. EGSR 2017. 28th Eurographics Symposium on Rendering, Helsinki, FIN, June 19-21, 2017

Variable-Size Batched Gauss-Huard for Block-Jacobi Preconditioning
Anzt, H.; Dongarra, J.; Flegar, G.; Quintana-Ortí, E. S.; Tomás, A. E.
2017. Procedia computer science, 108, 1783–1792. doi:10.1016/j.procs.2017.05.186

Flexible batched sparse matrix-vector product on GPUs
Anzt, H.; Collins, G.; Dongarra, J.; Flegar, G.; Quintana-Ortí, E. S.
2017. the 8th Workshop, Denver, Colorado, 12–17 November 2017, 1–8, Association for Computing Machinery (ACM). doi:10.1145/3148226.3148230

Biomolecular Coevolution and its Applications : Going from Structure Prediction Toward Signaling, Epistasis, and Function
Zerihun, M. B.; Schug, A.
2017. Biochemical Society transactions, 45 (6), 1253–1261. doi:10.1042/BST20170063

Overcoming Load Imbalance for Irregular Sparse Matrices
Flegar, G.; Anzt, H.
2017. Proceedings of the 7th Workshop on Irregular Applications : Architectures and Algorithms, IA3’17, Denver, Colorado, USA, 12th - 17th November 2017, Art.Nr. 2, Association for Computing Machinery (ACM). doi:10.1145/3149704.3149767

The Swiss Army Knife of Job Submission Tools : Grid-control
Stober, F.; Fischer, M.; Schleper, P.; Stadie, H.; Garbers, C.; Lange, J.; Kovalchuk, N.
2017. Journal of physics / Conference Series, 898 (9), Art.Nr. 092052. doi:10.1088/1742-6596/898/9/092052

RootJS : Node.js Bindings for ROOT 6
Beffart, T.; Früh, M.; Haas, C.; Rajgopal, S.; Schwabe, J.; Wolff, C.; Szuba, M.
2017. Journal of physics / Conference Series, 898 (7), Art.Nr. 072028. doi:10.1088/1742-6596/898/7/072028

One-stop publishing and archiving: Forschungsdaten für Promotionsvorhaben über Repositorien publizieren und archivieren: Eine landesweite Initiative im Rahmen des Projekts bwDataDiss am Beispiel des Karlsruher Instituts für Technologie (KIT)
Kurze, T.; Tobias, R.; Bonn, M.
2017. E-Science-Tage 2017: Forschungsdaten managen. Hrsg.: J. Kratzke, Heidelberger E-Books (heiBOOKS)

Vorwort der Herausgeber
Kratzke, J.; Heuveline, V.
2017. E-Science-Tage 2017: Forschungsdaten managen. Hrsg.: J. Kratzke, Heidelberger E-Books (heiBOOKS)

Erfassung und Speicherung von Forschungsdaten im Fachbereich Chemie: Bereitstellung moderner Forschungs-infrastrukturen durch ein elektronisches Laborjournal mit Repositorium-Anbindung
Jung, N.; Tremouilhac, P.; Kramer, C.; Potthoff, J.
2017. E-Science-Tage 2017: Forschungsdaten managen. Hrsg.: J. Kratzke, 127–136, Heidelberger E-Books (heiBOOKS)

Diurnal variations of BrONO₂ observed by MIPAS-B at midlatitudes and in the Arctic
Wetzel, G.; Oelhaf, H.; Höpfner, M.; Friedl-Vallon, F.; Ebersoldt, A.; Gulde, T.; Kazarski, S.; Kirner, O.; Kleinert, A.; Maucher, G.; Nordmeyer, H.; Orphal, J.; Ruhnke, R.; Sinnhuber, B.-M.
2017. Atmospheric chemistry and physics, 17 (23), 14631–14643. doi:10.5194/acp-17-14631-2017

Benchmarking Cloud Resources for HEP
Alef, M.; Cordeiro, C.; Salvo, A. de; Di Girolamo, A.; Field, L.; Giordano, D.; Guerri, M.; Schiavi, F. C.; Wiebalck, A.
2017. Journal of physics / Conference Series, 898. doi:10.1088/1742-6596/898/9/092056

Measurements of , , and spectra in proton-proton interactions at 20, 31, 40, 80 and 158 GeV/ with the NA61/SHINE spectrometer at the CERN SPS
NA61/SHINE Collaboration; Aduszkiewicz, A.; Ali, Y.; Andronov, E.; Antićić, T.; Baatar, B.; Baszczyk, M.; Bhosale, S.; Blondel, A.; Bogomilov, M.; Brandin, A.; Bravar, A.; Brzychczyk, J.; Bunyatov, S. A.; Busygina, O.; u. a.
2017. The European physical journal / C, 77 (10), Art.Nr. 671. doi:10.1140/epjc/s10052-017-5260-4

Competitive reactivity of nitrogen and oxygen with nickel when an argon/air mixture is used as sputtering gas
Poulopoulos, P.; Sousanis, A.; Zotos, K. C.; Papaefstathiou, N.; Grammatikopoulos, S.; Trachylis, D.; Schommers, W.; Meletis, E. I.; Politis, C.
2017. Journal of nanoscience and nanotechnology, 17 (12), 8842–8849. doi:10.1166/jnn.2017.15209

Maxent-stress optimization of 3D biomolecular models
Wegner, M.; Taubert, O.; Schug, A.; Meyerhenke, H.
2017. 25th European Symposium on Algorithms, Vienna, A, 4.- 6. September 2017, Art.Nr.: 70, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (LZI). doi:10.4230/LIPIcs.ESA.2017.70

Significance of Nanopatterned and Clustered DLL1 for Hematopoietic Stem Cell Proliferation
Winkler, A.-L.; Wulffen, J. von; Rödling, L.; Raic, A.; Reinartz, I.; Schug, A.; Gralla-Koser, R.; Geckle, U.; Welle, A.; Lee-Thedieck, C.
2017. Advanced functional materials, 27 (21), Art.Nr. 1606495. doi:10.1002/adfm.201606495

Burner design for an industrial furnace for thermal post-combustion
Denev, J. A.; Dinkov, I.; Bockhorn, H.
2017. Energy procedia, 120, 484–491. doi:10.1016/j.egypro.2017.07.171

Long-term Access to Data, Communities, Developments and Infrastructure
Van Wezel, J.; Bach, F.; Krauss, P.; Kurze, T.; Meyer, J.; Müller-Pfefferkorn, R.; Potthoff, J.
2017. Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA). Ed.: C. Jung, 125–140, KIT Scientific Publishing

Federated Storage Infrastructure for LSDMA
Ertl, B.; Fuhrmann, P.; Hardt, M.; Millar, P.; Mkrtchan, T.; Schwank, K.; Sahakya, M.; Wegh, B.
2017. Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA). Ed.: C. Jung, 99–107, KIT Scientific Publishing

Federated Authentication and Authorization Infrastructure for LSDMA
Hardt, M.; Hayrapetyan, A.; Fuhrmann, P.; Millar, P.
2017. Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA). Ed.: C. Jung, 85–97, KIT Scientific Publishing

Web Processing Services for the Climate Science Community supported by Birdhouse
Ehbrecht, C.; Kindermann, S.; Meyer, J.
2017. Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA). Ed.: C. Jung, 11–22, KIT Scientific Publishing

Analysis of Environmental Satellite Data with Full Stack of Web Applications
Szuba, M.; Ameri, P.; Meyer, J.
2017. Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA). Ed.: C. Jung, 1–9, KIT Scientific Publishing

Network robustness assessed within a dual connectivity framework : Joint dynamics of the Active and Idle Networks
Tejedor, A.; Longjas, A.; Zaliapin, I.; Ambroj, S.; Foufoula-Georgiou, E.
2017. Scientific reports, 7 (1), Art.Nr. 8567. doi:10.1038/s41598-017-08714-3

Transforming a Local Medical Image Analysis for Running on a Hadoop Cluster
Strutz, M.; Heßling, H.; Streit, A.
2017. Procedia computer science, 108, 1622–1631. doi:10.1016/j.procs.2017.05.227

Numerical Simulation of the Ignition of Fuel/Air Gas Mixtures Around Small Hot Particles
Häber, T.; Zirwes, T.; Roth, D.; Zhang, F.; Bockhorn, H.; Maas, U.
2017. Zeitschrift für physikalische Chemie, 231 (10), 1625–1654. doi:10.1515/zpch-2016-0933

Combination of D0 measurements of the top quark mass
D0 Collaboration; Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Aushev, V.; Aushev, Y.; u. a.
2017. Physical review / D, 95 (11), Art.Nr.: 112004. doi:10.1103/PhysRevD.95.112004

Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA)
Jung, C.; Meyer, J.; Streit, A. (Hrsg.)
2017. KIT Scientific Publishing. doi:10.5445/KSP/1000071931

An emission module for ICON-ART 2.0: implementation and simulations of acetone
Weimer, M.; Schröter, J.; Eckstein, J.; Deetz, K.; Neumaier, M.; Fischbeck, G.; Hu, L.; Millet, D. B.; Rieger, D.; Vogel, H.; Vogel, B.; Reddmann, T.; Kirner, O.; Ruhnke, R.; Braesicke, P.
2017. Geoscientific model development, 10 (6), 2471–2494. doi:10.5194/gmd-10-2471-2017

Using adaptive resource allocation to implement an elastic MapReduce framework
Zhao, J.; Xue, C.; Tao, X.; Zhang, S.; Tao, J.
2017. Software <Chichester>, 47 (3), 349–360. doi:10.1002/spe.2398

Trusted Performance Analysis on Systems With a Shared Memory
Zhao, J.; Xue, C.; Tao, J.; Ranjan, R.; Kolodziej, J.; Wang, L.; Chen, D.
2017. IEEE systems journal, 11 (1), 272–282. doi:10.1109/JSYST.2014.2365234

Effect of unsteady stretching on the flame local dynamics
Zhang, F.; Zirwes, T.; Habisreuther, P.; Bockhorn, H.
2017. Combustion and flame, 175, 170–179. doi:10.1016/j.combustflame.2016.05.028

Scalability and performance of the Privacy-Aware Classification method GenPAC
Schlitter, N.; Ullrich, M.; Lassig, J.
2017. 14th Annual Conference on Privacy, Security and Trust (PST), Auckland, New Zealand, 12th - 14th December 2016, 376–383, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PST.2016.7906959

Large-scale identification of coevolution signals across homo-oligomeric protein interfaces by direct coupling analysis
Uguzzoni, G.; Lovis, S. J.; Oteri, F.; Schug, A.; Szurmant, H.; Weigt, M.
2017. Proceedings of the National Academy of Sciences of the United States of America, 114 (13), E2662-E2671. doi:10.1073/pnas.1615068114

Activity and electrochemical stability of a chromium modified nickel catalyst for oxygen reduction reaction
Kondov, I.; Faubert, P.; Müller, C.
2017. Electrochimica acta, 236, 260–272. doi:10.1016/j.electacta.2017.03.123

Computational Insights into Zebrafish Brain Development during Gastrulation. Dissertation
Sinner, C.
2017. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000068105

HEPPA-II model–measurement intercomparison project: EPP indirect effects during the dynamically perturbed NH winter 2008-2009
Funke, B.; Ball, W.; Bender, S.; Gardini, A.; Harvey, V. L.; Lambert, A.; López-Puertas, M.; Marsh, D. R.; Meraner, K.; Nieder, H.; Päivärinta, S.-M.; Pérot, K.; Randall, C. E.; Reddmann, T.; Rozanov, E.; u. a.
2017. Atmospheric chemistry and physics, 17 (5), 3573–3604. doi:10.5194/acp-17-3573-2017

On MAS-Based, Scalable Resource Allocation in Large-Scale, Dynamic Environments
Gudu, D.; Hardt, M.; Streit, A.
2017. The 13th IEEE International Conference on Ubiquitous Intelligence and Computing, The 13th IEEE International Conference on Advanced and Trusted Computing, The 16th IEEE International Conference on Scalable Computing and Communications, The IEEE International Conference on Cloud and Big Data Computing, The IEEE International Conference on Internet of People, The IEEE Smart World Congress and Workshops, Toulouse, F, July 18-21, 2016. Ed.: D. El Baz, 567–574, IEEE Computer Society. doi:10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0097

An assessment of the climatological representativeness of IAGOS-CARIBIC trace gas measurements using EMAC model simulations
Eckstein, J.; Ruhnke, R.; Zahn, A.; Neumaier, M.; Kirner, O.; Braesicke, P.
2017. Atmospheric chemistry and physics, 17 (4), 2775–2794. doi:10.5194/acp-17-2775-2017

Combustion-Generated Noise : An Environment-Related Issue for Future Combustion Systems
Zhang, F.; Zirwes, T.; Nawroth, H.; Habisreuther, P.; Bockhorn, H.; Paschereit, C. O.
2017. Energy technology, 5 (7), 1045–1054. doi:10.1002/ente.201600526

Initiation of deep convection in the Sahel in a convection-permitting climate simulation for northern Africa
Maurer, V.; Bischoff-Gauß, I.; Kalthoff, N.; Gantner, L.; Roca, R.; Panitz, H.-J.
2017. Quarterly journal of the Royal Meteorological Society, 143 (703), 806–816. doi:10.1002/qj.2966

Realtime Analysis of Large-Scale Data. Dissertation
Becker, D.
2017. KIT Scientific Publishing. doi:10.5445/KSP/1000056498

Scale-Dependent Priors for Variance Parameters in Structured Additive Distributional Regression
Klein, N.; Kneib, T.
2016. Bayesian Analysis, 11 (4), 1071–1106. doi:10.1214/15-BA983

Measurement of the inclusive t t production cross section in p p collisions at s =1.96 TeV and determination of the top quark pole mass
D0 Collaboration; Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Aushev, Y.; Avila, C.; u. a.
2016. Physical review / D, 94 (9), Art. Nr.: 092004. doi:10.1103/PhysRevD.94.092004

Analysing farmland rental rates using Bayesian geoadditive quantile regression
März, A.; Klein, N.; Kneib, T.; Musshoff, O.
2016. European Review of Agricultural Economics, 43 (4), 663–698. doi:10.1093/erae/jbv028

Modelling Hospital Admission and Length of Stay by Means of Generalised Count Data Models
Herwartz, H.; Klein, N.; Strumann, C.
2016. Journal of Applied Econometrics, 31 (6), 1159–1182. doi:10.1002/jae.2454

Heat and Mass Transfer during Condensation of Fast Pyrolysis Vapors
Ille, Y.; Hamberger, P.; Dahmen, N.; Schaber, K.
2016. Chemie - Ingenieur - Technik, 88 (9), 1235. doi:10.1002/cite.201650162

Measurement of the top quark mass using the matrix element technique in dilepton final states
D0 Collaboration; Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Aushev, V.; Aushev, Y.; u. a.
2016. Physical review / D, 94 (3), 032004. doi:10.1103/PhysRevD.94.032004

Molecular Origin of the Charge Carrier Mobility in Small Molecule Organic Semiconductors
Friederich, P.; Meded, V.; Poschlad, A.; Neumann, T.; Rodin, V.; Stehr, V.; Symalla, F.; Danilov, D.; Lüdemann, G.; Fink, R. F.; Kondov, I.; Wrochem, F. von; Wenzel, W.
2016. Advanced functional materials, 26 (31), 5757–5763. doi:10.1002/adfm.201601807

Evidence for a π State
D0 Collaboration; Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Aushev, V.; Aushev, Y.; u. a.
2016. Physical review letters, 117 (2), Art.Nr. 022003. doi:10.1103/PhysRevLett.117.022003

B0s lifetime measurement in the CP-odd decay channel B0s→J/ψ f0(980)
D0 Collaboration; Abazov, V. M.
2016. Physical review / D, 94 (1), 012001. doi:10.1103/PhysRevD.94.012001

Simultaneous inference in structured additive conditional copula regression models: a unifying Bayesian approach
Klein, N.; Kneib, T.
2016. Statistics and Computing, 26 (4), 841–860. doi:10.1007/s11222-015-9573-6

Measurement of spin correlation between top and antitop quarks produced in at √s = 1.96 TeV
D0 Collaboration; Abazov, V. M.
2016. Physics letters / B, 757, 199–206. doi:10.1016/j.physletb.2016.03.053

Evidence for Simultaneous Production of J /ψ and Y Mesons
D0 Collaboration; Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Aushev, V.; Avila, C.; u. a.
2016. Physical review letters, 116 (8), Art.Nr. 082002. doi:10.1103/PhysRevLett.116.082002

Measurement of the forward-backward asymmetry of Λ and Λ ¯ production in p p ¯ collisions
D0 Collaboration; Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Avila, C.; Badaud, F.; u. a.
2016. Physical review / D, 93 (3), Art. Nr.: 032002. doi:10.1103/PhysRevD.93.032002

Corridors restore animal-mediated pollination in fragmented tropical forest landscapes
Kormann, U.; Scherber, C.; Tscharntke, T.; Klein, N.; Larbig, M.; Valente, J. J.; Hadley, A. S.; Betts, M. G.
2016. Proceedings of the Royal Society B: Biological Sciences, 283 (1823), 20152347. doi:10.1098/rspb.2015.2347

Precise measurement of the top quark mass in dilepton decays using optimized neutrino weighting
Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Avila, C.; Badaud, F.; Bagby, L.; u. a.
2016. Physics letters / B, 752, 18–26. doi:10.1016/j.physletb.2015.10.086

Exploring Opportunities for Job-temporal File Systems with ADA-FS
Oeste, S.; Kluge, M.; Soysal, M.; Streit, A.; Vef, M.-A.; Brinkmann, A.
2016. 1st Joint International Workshop on Parallel Data Storage and Data Intensive Scalable Computing Systems (PDSW-DISCS 2016), Salt Lake City, UT, November 14, 2016

Consideration of values in the design of access control systems
Neudecker, T.; Hayrapetyan, A.; Degitz, A.; Andelfinger, P.
2016. 46. Jahrestagung der Gesellschaft fur Informatik - 46th Annual Meeting of the German Informatics Society, INFORMATIK 2016; Klagenfurt; Austria; 26 September 2016 through 30 September 2016. Ed.: H. C. Mayr, 275–288, Gesellschaft für Informatik (GI)

INDIGO-Datacloud: a Cloud-based Platform as a Service oriented to scientific computing for the exploitation of heterogeneous resources
Salomoni, D.; Donvito, G.; Campos Plasencia, I.; Marco, J.; Oliveira Gomes, J.; Gaido, L.; Dutka, L.; Plociennik, M.; Hardt, M.; Fuhrmann, P.; Barbera, R.
2016. 22nd International Conference on Computing in High Energy, Nuclear Physics (CHEP2016), San Francisco, CA, October 8-14, 2016

Storage Quality-of-Service in Cloud-based Scientific Environments: a Standardization Approach
Miller, P.; Fuhrmann, P.; Hardt, M.; Ertl, B.; Brzezniak, M.
2016. 22nd International Conference on Computing in High Energy, Nuclear Physics (CHEP2016), San Francisco, CA, October 10-14, 2016

The INDIGO-DataCloud authentication, authorisation infrastructure
Ceccanti, A.; Wegh, B.; Ertl, B.; Vianello, E.; Caberletti, M.; Hardt, M.; Millar, P.; Licehammer, S.
2016. 22nd International Conference on Computing in High Energy, Nuclear Physics (CHEP2016), San Francisco, CA, October 8-14, 2016

Realtime Analysis of Large-Scale Data [Finale Version]. Dissertation
Becker, D.
2016. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000069259

Bwcloud: Cross-site server virtualization
Dulov, O. V.
2016. 7th International Conference Distributed Computing and Gridtechnologies in Science and Education (GRID 2016), Dubna, Russian Federation, July 4-9, 2016. Ed.: V. Korenkov, 202–212, RWTH Aachen

MAS-based, scalable allocation of resources in large-scale, dynamic environments
Gudu, D.
2016. KIT>>Links(opens in a new window)| BibTeX export | Download | Add to List | More... Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, Singapore, SGP, May 9-13, 2016, 1530–1531, International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)

Identity harmonization for federated HPC, grid and cloud services
Ertl, B.; Stevanovic, U.; Hayrapetyan, A.; Wegh, B.; Hardt, M.
2016. 2016 International Conference on High Performance Computing & Simulation (HPCS), Innsbruck, Austria, 18–22 July 2016, 621–627, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/HPCSim.2016.7568393

Timing Analysis for Inferring the Topology of the Bitcoin Peer-to-Peer Network
Neudecker, T.; Andelfinger, P.; Hartenstein, H.
2016. The 13th IEEE International Conference on Ubiquitous Intelligence and Computing, The 13th IEEE International Conference on Advanced and Trusted Computing, The 16th IEEE International Conference on Scalable Computing and Communications, The IEEE International Conference on Cloud and Big Data Computing, The IEEE International Conference on Internet of People, The IEEE Smart World Congress and Workshops, Toulouse, F, July 18-21, 2016. Ed.: D. El Baz, 358–367, IEEE Computer Society. doi:10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0070

Energy-efficient task scheduling in data centers
Mhedheb, Y.; Streit, A.
2016. 6th International Conference on Cloud Computing and Services Science, CLOSER 201, Rome, Italy, 23 - 25 April, 2016, 273–282, Science and Technology Publications

Realtime-processing of nanocrystallography images
Becker, D.; Streit, A.
2016. Proceedings of the 18th International Conference on Computer Modelling and Simulation (UKSim-AMSS), Cambridge, UK, April 6-8,2016. Ed.: G. Jenkins, 190–195, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/UKSim.2016.20

Research Data Management within the E-Science Strategy in Baden-Württemberg - Preliminary Results of Project bwFDM-Communities
Cayoglu, U.; Shcherbakov, D.; Tristram, F.
2016. Proceedings of the 2nd Data Management Workshop, 1–6, Geographisches Institut. doi:10.5880/TR32DB.KGA96.2

Erratum: Search for Violation of CPT and Lorentz Invariance in Bs0 Meson Oscillations (Physical Review Letters (2015) 115 (161601))
D0 Collaboration; Abazov, V. M.; Alton, A.; Burdin, S.; Deterre, C.; Grohsjean, A.; La Cruz, I. H.-D.; Partridge, R.; Hesketh, G.; Luna-Garcia, R.; Santos, A. S.; Meyer, J.; Patwa, A.; Cooke, M.; Borysova, M.; u. a.
2016. Physical review letters, 116 (1), Art. Nr.: 019901. doi:10.1103/PhysRevLett.116.019901

Two-Zone Fluidized Bed Reactors for Butadiene Production: A Multiphysical Approach with Solver Coupling for supercomputing Application
Matthias Hettel; Jordan A. Denev; Olaf Deutschmann
2016. High Performance Computing in Science & Engineering - 19th Results and Review Workshop of the HLRS

Impact of infinite thin flame approach on the evaluation of flame speed using spherically expanding flames
Zhang, F.; Baust, T.; Zirwes. Torsten; Denev, J. A.; Habisreuther, P.; Zarzalis, N.; Bockhorn, H.
2016. Energy technology, 5 (7), 1055–1063. doi:10.1002/ente.201600573

A scalable architecture for online anomaly detection of WLCG batch jobs
Kuehn, E.; Fischer, M.; Giffels, M.; Jung, C.; Petzold, A.
2016. Journal of physics / Conference Series, 762, 012002. doi:10.1088/1742-6596/762/1/012002

Data Locality via Coordinated Caching for Distributed Processing
Fischer, M.; Kuehn, E.; Gffels, M.; Jung, C.
2016. Journal of physics / Conference Series, 762, 012011. doi:10.1088/1742-6596/762/1/012011

NoWog: A Workload Generator for Database Performance Benchmarking
Ameri, P.; Schlitter, N.; Meyer, J.; Streit, A.
2016. 2016 IEEE 14th Intl Conf on Dependable, Autonomic and Secure Computing, 14th Intl Conf on Pervasive Intelligence and Computing, 2nd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech), Auckland, New Zealand, 8–12 August 2016. Ed. : Q. Jin, 666–673, IEEE Computer Society. doi:10.1109/DASC-PICom-DataCom-CyberSciTec.2016.120

Online Distance Measurement for Tree Data Event Streams
Kuehn, E.; Streit, A.
2016. 2016 IEEE 14th Intl Conf on Dependable, Autonomic and Secure Computing, 14th Intl Conf on Pervasive Intelligence and Computing, 2nd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech), Auckland, New Zealand, 8–12 August 2016. Ed. : Q. Jin, 681–688, IEEE Computer Society. doi:10.1109/DASC-PICom-DataCom-CyberSciTec.2016.122

Errors induced by different approximations in handling horizontal atmospheric inhomogeneities in MIPAS/ENVISAT retrievals
Castelli, E.; Ridolfi, M.; Carlotti, M.; Sinnhuber, B.-M.; Kirner, O.; Kiefer, M.; Dinelli, B. M.
2016. Atmospheric measurement techniques, 9 (11), 5499–5508. doi:10.5194/amt-9-5499-2016

The RADAR project-a service for research data archival and publication
Kraft, A.; Razum, M.; Potthoff, J.; Porzel, A.; Engel, T.; Lange, F.; den Broek, K. van; Furtado, F.
2016. ISPRS International Journal of Geo-Information, 5 (3), Art.Nr.: 28. doi:10.3390/ijgi5030028

Study of double parton interactions in diphoton+dijet events in p p collisions at s =1.96 TeV
D0 Collaboration; Abazov, V. M.; Abbott, B.; Acharya, B. S.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Aushev, V.; Aushev, Y.; u. a.
2016. Physical review / D, 93 (5), Art.Nr.: 052008. doi:10.1103/PhysRevD.93.052008

Graph-based decision making for task scheduling in concurrent Gaudi
Shapoval, I.; Clemencic, M.; Hegner, B.; Funke, D.; Piparo, D.; Mato, P.
2016. IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), San Diego, California, USA, 31 Oct.-7 Nov. 2015, 1–3, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/NSSMIC.2015.7581843

Energy Efficient Runtime Framework for Exascale Systems
Mhedheb, Y.; Streit, A.
2016. High Performance Computing (ISC), 32–44, Springer-Verlag. doi:10.1007/978-3-319-46079-6_3

A new module for trace gas emissions in ICON-ART 2.0: A sensitivity study focusing on acetone emissions and concentrations
Weimer, M.; Schröter, J.; Eckstein, J.; Deetz, K.; Neumaier, M.; Fischbeck, G.; Rieger, D.; Vogel, H.; Vogel, B.; Reddmann, T.; Kirner, O.; Ruhnke, R.; Braesicke, P.
2016. Geoscientific model development discussions, 2016, 1–27. doi:10.5194/gmd-2016-259

Einsatz von ITSM in Projektform – Erfahrungsberichte
Beckmann, N.; Brenner, M.; Bündgens, D.; Grindler, A.; Hengstebeck, I.; Holler, B.; Lara, C.; Mai, M.; Peinz, H.; Springorum, L.
2016. Kooperation von Rechenzentren : Governance und Steuerung - Organisation, Rechtsgrundlagen, Politik. Hrsg.: D. von Suchodoletz, 109–126, Oldenbourg Verlag. doi:10.1515/9783110459753-008

On the climatological probability of the vertical propagation of stationary planetary waves
Karami, K.; Braesicke, P.; Sinnhuber, M.; Versick, S.
2016. Atmospheric chemistry and physics, 16 (13), 8447–8460. doi:10.5194/acp-16-8447-2016

A semi-empirical model for mesospheric and stratospheric NOy produced by energetic particle precipitation
Funke, B.; Lopez-Puertas, M.; Stiller, G. P.; Versick, S.; Clarmann, T. von
2016. Atmospheric chemistry and physics, 16 (13), 8667–8693. doi:10.5194/acp-16-8667-2016

Enabling collaborative MapReduce on the Cloud with a single-sign-on mechanism
Zhao, J.; Tao, J.; Streit, A.
2016. Computing, 98 (1-2), 55–72. doi:10.1007/s00607-014-0390-0

MAS-based, scalable allocation of resources in large-scale, dynamic environments (Doctoral consortium)
Gudu, D.
2016. Proceedings of the 2016 International Conference on Agents and Multiagent Systems (AAMAS’16), Singapore, SGP, May 9-13, 2016, 1530–1531, International Foundation for Autonomous Agents and Multiagent Systems

A Distributed System for Storing and Processing Data from Earth-Observing Satellites: System Design and Performance Evaluation of the Visualisation Tool
Szuba, M.; Ameri, P.; Grabowski, U.; Meyer, J.; Streit, A.
2016. Proceedings of the 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2016), Cartagena de Indias, Colombia, May 16-19, 2016, 169–174, IEEE Computer Society. doi:10.1109/CCGrid.2016.19

Direct Neutrino Mass Experiments
Mertens, S.
2016. Journal of physics / Conference Series, 718, 022013/1–9. doi:10.1088/1742-6596/718/2/022013

Privileged Scaffolds in Medicinal Chemistry - A Computational Approach
Anand, P.; John, S.; Meliciani, I.; Schug, A.; Wenzel, W.
2016. Privileged Scaffolds in Medicinal Chemistry : Design, Synthesis, Evaluation. Ed.: S. Bräse, 16–63, Royal Society of Chemistry (RSC). doi:10.1039/9781782622246-00016

Database Techniques for Big Data
Ameri, P.
2016. Big Data : Principles and Paradigms. Ed.: R. Buyya, 139–159, Morgan Kaufmann Publishers. doi:10.1016/B978-0-12-805394-2.00006-4

Data locality via coordinated caching for distributed processing
Fischer, M.; Kuehn, E.
2016. 7th International Conference on Cloud Computing, GRIDs, and Virtualization, Roma, I, March 20-24, 2016. Ed.: C. Becker Westphall, 113–118, International Academy, Research, and Industry Association (IARIA)

Decentralized secure data sharing with attribute-based encryption: A resource consumption analysis
Kuehner, H.; Hartenstein, H.
2016. Proceedings of the 4th ACM International Workshop on Security in Cloud Computing, SCC 2016, Xi’an, China, 30th May 2016, 74–81, Association for Computing Machinery (ACM). doi:10.1145/2898445.2898449

On a self-tuning index recommendation approach for databases
Ameri, P.
2016. 32nd IEEE International Conference on Data Engineering Workshops (ICDEW) Helsinki; Finland; 16 - 20 May 2016, 201–205, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICDEW.2016.7495648

Challenges of Index Recommendation for Databases : [With Specific Evaluation on a NoSQL Database]
Ameri, P.
2016. 2016 GI-Workshop Grundlagen von Datenbanken, vom 24.05.2016 bis zum 27.05.2016 in Nörten-Hardenberg, Niedersachsen, Deutschland, 10–14

Automation strategies for large-scale 3D image analysis
Stegmaier, J.; Schott, B.; Hübner, E.; Traub, M.; Shahid, M.; Takamiya, M.; Kobitski, A.; Hartmann, V.; Stotzka, R.; Van Wezel, J.; Streit, A.; Nienhaus, G. U.; Strähle, U.; Reischl, M.; Mikut, R.
2016. Automatisierungstechnik, 64 (7), 555–566. doi:10.1515/auto-2016-0019

Advances in Methods and Techniques for Processing Streaming Big Data in Datacentre Clouds
Ranjan, R.; Wang, L.; Zomaya, A. Y.; Tao, J.; Jayaraman, P. P.; Georgakopoulos, D.
2016. IEEE transactions on emerging topics in computing, 4 (2), 262–265. doi:10.1109/TETC.2016.2524219

Realtime Analysis of Large-Scale Data [Vorläufige Version]. Dissertation
Becker, D.
2016. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000057693

Multiscale simulation of organic electronics via smart scheduling of quantum mechanics computations
Friederich, P.; Strunk, T.; Wenzel, W.; Kondov, I.
2016. Procedia Computer Science, 80, 1244–1254. doi:10.1016/j.procs.2016.05.495

On a dynamic scheduling algorithm for massively parallel computations of atomic isotopes
Dorofeeva, E.; Arora, J.; Typel, S.; Poghosyan, G.; Sanders, P.; Streit, A.
2016. 7th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2016), Hersonissos, GR, June 5-10, 2016. Proceedings published online

Measurement of the forward-backward asymmetries in the production of Ξ and Ω baryons in pp¯ collisions
D0 Collaboration; Abazov, V. M.; Abbott, B.; Acharya, B.; Adams, M.; Adams, T.; Agnew, J. P.; Alexeev, G. D.; Alkhazov, G.; Alton, A.; Askew, A.; Atkins, S.; Augsten, K.; Aushev, V.; Aushev, Y.; u. a.
2016. Physical review / D, 93 (11), 112001. doi:10.1103/PhysRevD.93.112001

Comparison of XCO abundances from the Total Carbon Column Observing Network and the Network for the Detection of Atmospheric Composition Change measured in Karlsruhe
Kiel, M.; Hase, F.; Blumenstock, T.; Kirner, O.
2016. Atmospheric measurement techniques, 9 (5), 2223–2239. doi:10.5194/amt-9-2223-2016

ARM Cluster for Performant and Energy-Efficient Storage
Gudu, D.; Hardt, M.
2016. Computational Sustainability. Ed.: J. Lässig, 265–276, Springer International Publishing. doi:10.1007/978-3-319-31858-5_12

Comparing data obtained from ground-based measurements of the total contents of O₃, HNO₃,HCl, and NO₂ and from their numerical simulation
Virolainen, Y. A.; Timofeyev, Y. M.; Polyakov, A. V.; Ionov, D. V.; Kirner, O.; Poberovskii, A. V.; Imhasin, H. K.
2016. Izvestiya - Atmospheric and Ocean Physics, 52 (1), 57–65. doi:10.1134/S0001433815060146

Earth system chemistry integrated modelling (ESCiMo) with the modular earth submodel system (MESSy) version 2.51
Jöckel, P.; Tost, H.; Pozzer, A.; Kunze, M.; Kirner, O.; Brenninkmeijer, C. A. M.; Brinkop, S.; Cai, D. S.; Dyroff, C.; Eckstein, J.; Frank, F.; Garny, H.; Gottschaldt, K.-D.; Graf, P.; Grewe, V.; u. a.
2016. Geoscientific Model Development, 9 (3), 1153–1200. doi:10.5194/gmd-9-1153-2016

Modeling haboob dust storms in large-scale weather and climate models
Pantillon, F.; Knippertz, P.; Marsham, J. H.; Panitz, H.-J.; Bischoff-Gauss, I.
2016. Journal of geophysical research / Atmospheres, 121 (5), 2090–2109. doi:10.1002/2015JD024349

Ab initio transport calculations for functionalized graphene flakes on a supercomputer
Walz, M.; Bagrets, A.; Evers, F.; Kondov, I.
2016. High Performance Computing in Science and Engineering ’15 : Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2015. Ed.: W.E. Nagel, 139–154, Springer. doi:10.1007/978-3-319-24633-8_9

A Novel Framework for Simulating Computing Infrastructure and Network Data Flows Targeted on Cloud Computing
Krauß, P.; Kurze, T.; Streit, A.; Neumair, B.
2016. CLOUD COMPUTING 2016. The Seventh International Conference on Cloud Computing, GRIDs, and Virtualization, March 20 - 24, 2016 Rome, Italy. Ed.: C. Becker Westphall, 30–37, International Academy, Research, and Industry Association (IARIA)

On Spatial Measures of Geographic Relevance for Geotagged Social Media Content
Wang, X.; Gaugel, T.; Keller, M.
2016. Big Data Analytics in the Social and Ubiquitous Context. 5th International Workshop on Modeling Social Media, MSM 2014, 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, Revised Selected Papers. Ed.: F. Janssen, 70–89, Springer. doi:10.1007/978-3-319-29009-6_4

Designing Fail-Safe and Traffic Efficient 802.11p-based Rear-End Collision Avoidance
An, N.; Mittag, J.; Hartenstein, H.
2016. Ad hoc Networks, 37 (P1), 3–13. doi:10.1016/j.adhoc.2015.08.006

Hedonic House Price Modeling Based on Multilevel Structured Additive Regression
Razen, A.; Brunauer, W.; Klein, N.; Lang, S.; Umlauf, N.
2015. Computational Approaches for Urban Environments. Ed.: M. Helbich, 97–122, Springer International Publishing. doi:10.1007/978-3-319-11469-9_5

Data-driven coarse graining in action: Modeling and prediction of complex systems
Krumscheid, S.; Pradas, M.; Pavliotis, G. A.; Kalliadasis, S.
2015. Physical Review E, 92 (4), Article no: 042139. doi:10.1103/PhysRevE.92.042139

A new framework for extracting coarse-grained models from time series with multiscale structure
Kalliadasis, S.; Krumscheid, S.; Pavliotis, G. A.
2015. Journal of Computational Physics, 296, 314–328. doi:10.1016/j.jcp.2015.05.002

Bayesian Structured Additive Distributional Regression for Multivariate Responses
Klein, N.; Kneib, T.; Klasen, S.; Lang, S.
2015. Journal of the Royal Statistical Society Series C: Applied Statistics, 64 (4), 569–591. doi:10.1111/rssc.12090

Bayesian Generalized Additive Models for Location, Scale, and Shape for Zero-Inflated and Overdispersed Count Data
Klein, N.; Kneib, T.; Lang, S.
2015. Journal of the American Statistical Association, 110 (509), 405–419. doi:10.1080/01621459.2014.912955

A Semiparametric Analysis of Conditional Income Distributions
Sohn, A.; Klein, N.; Kneib, T.
2015. Journal of Contextual Economics – Schmollers Jahrbuch, 135 (1), 13–22. doi:10.3790/schm.135.1.13

Ultra-high energy air shower simulation without thinning in CORSIKA
Pierog, T.; Engel, R.; Heck, D.; Poghosyan, G.; Oehlschläger, J.; Veberic, D.
2015. 34th International Cosmic Ray Conference, ICRC 2015, The Hague, NL, 30. July - 6. August, 2015, Art.Nr.: 528, Scuola Internazionale Superiore di Studi Avanzati (SISSA)

Clustering evolving batch system jobs for online anomaly detection
Kuehn, E.
2015. 15th IEEE International Conference on Data Mining, Atlantic City, NJ, November 14-17, 2015. Ed.: P. Cui, 1534–1535, IEEE Computer Society. doi:10.1109/ICDMW.2015.219

Artificial Neural Network support to monitoring of the evolutionary driven security aware scheduling in computational distributed environments
Grzonka, D.; Kolodziej, J.; Tao, J.; Khan, S. U.
2015. Future generation computer systems, 51, 72–86. doi:10.1016/j.future.2014.10.031

A note on new trends in data-aware scheduling and resource provisioning in modern HPC systems : (Editorial)
Tao, J.; Kolodziej, J.; Ranjan, R.; Jayaraman, P. P.; Buyya, R.
2015. Future generation computer systems, 51, 45–46. doi:10.1016/j.future.2015.04.016

Revealing the global map of protein folding space by large-scale simulations
Sinner, C.; Lutz, B.; Verma, A.; Schug, A.
2015. The journal of chemical physics, 143 (24), Art.Nr.:243154. doi:10.1063/1.4938172

Constructing a folding model for protein S6 guided by native fluctuations deduced from NMR structures
Lammert, H.; Noel, J. K.; Haglund, E.; Schug, A.; Onuchic, J. N.
2015. The journal of chemical physics, 143 (24), Art.Nr. 243141. doi:10.1063/1.4936881

Unlocking data: Federated identity with LSDMA and dCache
Millar, A. P.; Behrmann, G.; Bernardt, C.; Fuhrmann, P.; Hardt, M.; Hayrapetyan, A.; Litvintsev, D.; Mkrtchyan, T.; Rossi, A.; Schwank, K.
2015. Journal of physics / Conference Series, 664 (4), 042037/1–4. doi:10.1088/1742-6596/664/4/042037

Benchmark of a cubieboard cluster
Schnepf, M. J.; Gudu, D.; Rische, B.; Fischer, M.; Jung, C.; Hardt, M.
2015. Journal of physics / Conference Series, 664 (5), 052032/1–7. doi:10.1088/1742-6596/664/5/052032

Real-time signal identification in photon science imaging
Becker, D.; Streit, A.
2015. International journal of simulation, 16 (3), 7.1–7.10. doi:10.1109/HPCSim.2015.7237101

An approach for integrating kerberized non web-based services with web-based identity federations
Bersenev, A. A.; Hayrapetyan, A.; Hardt, M.; Simon, M. E.
2015. Proceedings of the 10th International Conference on Software Paradigm Trends, Colmar, Alsace, France, 20 - 22 July, 2015 , [part of: ICSOFT 2015, 10th International Joint Conference on Software Technologies], 144–150, SciTePress

Localization of Signal Peaks in Photon Science Imaging
Becker, D.; Streit, A.
2015. 2015 17th UKSIM-AMSS International Conference on Modelling and Simulation, Cambridge, United Kingdom 25-27 March 2015. Ed.: D. Al-Dabass, 296–301, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/uksim.2015.35

Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1
Figliuzzi, M.; Jacquier, H.; Schug, A.; Tenaillon, O.; Weigt, M.
2015. Molecular Biology and Evolution, 33 (1), 268–280. doi:10.1093/molbev/msv211

On the Resource Consumption of Secure Data Sharing
Kühner, H.; Hartenstein, H.
2015. Trustcom/BigDataSE/ISPA, IEEE, Helsinki, finland, 20-22. August 2015. Vol. 1, 880–889, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/Trustcom.2015.460

A Security Analysis of the Emerging P2P-based Personal Cloud Platform MaidSafe
Jacob, F.; Mittag, J.; Hartenstein, H.
2015. Proceedings of the IEEE Trustcom / BigDataSE / ISPA : Helsinki, Finland, 20th - 22nd August 2015, 1403–1410, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/Trustcom.2015.538

GridKa school - teaching information technologies since 2003
Ernst, M.; Hartmann, T.; Heiss, A.; Jung, C.; Meyer, J.; Nilsen, D.; Petzold, A.; Pfeiler, C. E.; Schaeffner, I.; Tao, J.; Weber, P.
2015. Proceedings of 2015 IEEE Global Engineering Conference (EDUCON), Tallinn, EST, March 18-20, 2015 Piscataway, N.J. : IEEE, 2015, 395–402. doi:10.1109/EDUCON.2015.7096003

Resilient FTS3 service at GridKa
Hartmann, T.; Bubeliene, J.; Hoeft, B.; Obholz, L.; Petzold, A.; Wisniewski, K.
2015. Journal of physics / Conference Series, 664 (6), 062019/1–7. doi:10.1088/1742-6596/664/6/062019

100G deployment @ (DE-KIT)
Hoeft, B.; Petzold, A.
2015. Journal of physics / Conference Series, 664 (5), 052017/1–8. doi:10.1088/1742-6596/664/5/052017

Integrating network and transfer metrics to optimize transfer efficiency and experiment workflows
McKee, S.; Babik, M.; Campana, S.; Di Girolamo, A.; Wildish, T.; Closier, J.; Roiser, S.; Grigoras, C.; Vukotic, I.; Salichos, M.; De, K.; Garonne, V.; Cruz, J. A. D.; Forti, A.; Walker, C. J.; u. a.
2015. Journal of physics / Conference Series, 664 (5), 052003/1–8. doi:10.1088/1742-6596/664/5/052003

The production deployment of IPv6 on WLCG
Bernier, J.; Campana, S.; Chadwick, K.; Chudoba, J.; Dewhurst, A.; Elias, M.; Fayer, S.; Finnern, T.; Grigoras, C.; Hartmann, T.; Hoeft, B.; Idiculla, T.; Kelsey, D. P.; Lopez-Munoz, F.; Macmahon, E.; u. a.
2015. Journal of physics / Conference Series, 664, 052018/1–8. doi:10.1088/1742-6596/664/5/052018

Preparing HPC applications for Exascale: challenges and recommendations
Abraham, E.; Bekas, C.; Brandic, I.; Genaim, S.; Johnsen, E. B.; Kondov, I.; Pllana, S.; Streit, A.
2015. 18th International Conference on Network-Based Information Systems, NBis 2015, Taipei, Taiwan, September 2-4, 2015, Barolli, L. [Hrsg.] Proceedings of the 18th International Conference on Network-Based Information Systems (NBiS), Taipei, Taiwan, September 2-4, 2015 Los Alamitos, Calif. : IEEE Computer Society, 2015, 401–406, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/NBiS.2015.61

Multicore job scheduling in the worldwide LHC computing grid
Forti, A.; Perez-Calero Yzquierdo, A.; Hartmann, T.; Alef, M.; Lahiff, A.; Templon, J.; Dal Pra, S.; Gila, M.; Skipsey, S.; Acosta-Silva, C.; Filipcic, A.; Walker, R.; Walker, C. J.; Traynor, D.; Gadrat, S.
2015. Journal of physics / Conference Series, 664 (6), 062016/1–8. doi:10.1088/1742-6596/664/6/062016

Progress in Multi-Disciplinary Data Life Cycle Management
Jung, C.; Gasthuber, M.; Giesler, A.; Hardt, M.; Meyer, J.; Prabhune, A.; Rigoll, F.; Schwarz, K.; Streit, A.
2015. Journal of physics / Conference Series, 664, 032018. doi:10.1088/1742-6596/664/3/032018

On a new approach to the index selection problem using mining algorithms
Ameri, P.; Meyer, J.; Streit, A.
2015. Proceedings of the 2015 IEEE International Conference on Big Data, Santa Clara, Calif., October 29 - November 1, 2015. Ed.: H. Ho, 2801–2910, IEEE Computer Society. doi:10.1109/BigData.2015.7364084

ICON-ART 1.0 - A new online-coupled model system from the global to regional scale
Rieger, D.; Bangert, M.; Bischoff-Gauss, I.; Förstner, J.; Lundgren, K.; Reinert, D.; Schröter, J.; Vogel, H.; Zängl, G.; Ruhnke, R.; Vogel, B.
2015. Geoscientific model development, 8 (6), 1659–1676. doi:10.5194/gmd-8-1659-2015

Data processing of high-rate low-voltage distribution grid recordings for smart grid monitoring and analysis
Maaß, H.; Cakmak, H. K.; Bach, F.; Mikut, R.; Harrabi, A.; Süß, W.; Jakob, W.; Stucky, K.-U.; Kühnapfel, U. G.; Hagenmeyer, V.
2015. EURASIP journal on advances in signal processing, 2015 (1), 1–21. doi:10.1186/s13634-015-0203-4

CloudBench - A framework for distributed, self-organizing, continuous and topology-aware IaaS cloud benchmarking with super-peer networks
Krauß, P.; Kurze, T.; Streit, A.
2015. Proceedings of the IEEE 11th International Conference on eScience, München, August 31 - September 4, 2014 Los Alamitos, Calif. : IEEE Computer Society, 2015, 273–278. doi:10.1109/eScience.2015.14

High performance data analysis via coordinated caches
Fischer, M.; Metzlaff, C.; Kühn, E.; Giffels, M.; Quast, G.; Jung, C.; Hauth, T.
2015. Journal of physics / Conference Series, 664 (9), 092008/1–8. doi:10.1088/1742-6596/664/9/092008

Active job monitoring in pilots
Kuehn, E.; Fischer, M.; Giffels, M.; Jung, C.; Petzold, A.
2015. Journal of physics / Conference Series, 664 (5), 052019/1–8. doi:10.1088/1742-6596/664/5/052019

A utility-based approach for customised cloud service selection
Jrad, F.; Tao, J.; Streit, A.; Knapper, R.; Flath, C.
2015. International journal of computational science and engineering, 10 (1), 32–44. doi:10.1504/IJCSE.2015.067056

A horizontally-scalable multiprocessing platform based on Node.js
Maatouki, A.; Meyer, J. T.; Szuba, M.; Streit, A.
2015. 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2015; Helsinki; Finland; 20 August 2015 - 22 August 2015, 100–107, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/Trustcom.2015.618

Partitioning and budget of inorganic and organic chlorine species observed by MIPAS-B and TELIS in the Arctic in March 2011
Wetzel, G.; Oelhaf, H.; Birk, M.; Lange, A. de; Engel, A.; Friedl-Vallon, F.; Kirner, O.; Kleinert, A.; Maucher, G.; Nordmeyer, H.; Orphal, J.; Ruhnke, R.; Sinnhuber, B.-M.; Vogt, P.
2015. Atmospheric chemistry and physics, 15 (14), 8065–8076. doi:10.5194/acp-15-8065-2015

Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction
De Leonardis, E.; Lutz, B.; Ratz, S.; Cocco, S.; Monasson, R.; Schug, A.; Weigt, M.
2015. Nucleic Acids Research, 43 (21), 10444–10455. doi:10.1093/nar/gkv932

Analyzing data flows of WLCG jobs at batch job level
Kuehn, E.; Fischer, M.; Giffels, M.; Jung, C.; Petzold, A.
2015. Journal of Physics: Conference Series, 608, 1–6. doi:10.1088/1742-6596/608/1/012017

Tier 3 batch system data locality via managed caches
Fischer, M.; Giffels, M.; Jung, C.; Kühn, E.; Quast, G.
2015. Journal of physics / Conference Series, 608 (1), Art.Nr. 012018/1–5. doi:10.1088/1742-6596/608/1/012018

Ein Ansatz zur automatisierten Erstellung umfangreicher und komplexer Simulationsmodelle für elektrische Übertragungsnetze aus OpenStreetMap-Daten = An attempt for fully automated generation of large-scale and complex simulation models for electrical transmission networks derived from OpenStreetMap data
Cakmak, H. K.; Maass, H.; Bach, F.; Kühnapfel, U.; Hagenmeyer, V.
2015. Automatisierungstechnik, 63 (11), 911–925. doi:10.1515/auto-2015-0046

Interaction networks in protein folding via atomic-resolution experiments and long-time-scale molecular dynamics simulations
Sborgi, L.; Verma, A.; Piana, S.; Lindorff-Larsen, K.; Cerminara, M.; Santiveri, C. M.; Shaw, D. E.; Alba, E. de; Munoz, V.
2015. Journal of the American Chemical Society, 137, 6506–6516. doi:10.1021/jacs.5b02324

Integrating molecular dynamics simulations with chemical probing experiments using SHAPE-FIT
Kirmizialtin, S.; Hennelly, S. P.; Schug, A.; Onuchic, J. N.; Sanbonmatsu, K. Y.
2015. Methods in enzymology, Kelman, Z. [Hrsg.] Isotope Labeling of Biomolecules : Labeling Methods Amsterdam [u.a.] : Elsevier / Academic Press, 2015 (Methods in Enzymology ; 553), 553, 215–234. doi:10.1016/bs.mie.2014.10.061

Grid engine at GridKa
Alef, M.
2015. HEPiX Spring 2015 Workshop, Oxford, GB, March 23-27, 2015 Transparencies publ.online

Fast benchmarks
Michelotto, M.; Alef, M.
2015. HEPiX Spring 2015 Workshop, Oxford, GB, March 23-27, 2015 Transparencies publ.online

HS06+ benchmark update
Alef, M.; Michelotto, M.
2015. Monthly Meeting of the WLCG Grid Deployment Board, Geneve, CH, January 14, 2015 Transparencies publ.online

Multicore job scheduling in the worldwide LHC computing grid
Forti, A.; Perez-Calero Yzquierdo, A.; Hartmann, T.; Alef, M.; Lahiff, A.; Templon, J.; Dal Pra, S.
2015. 21st International Conference on Computing in High Energy and Nuclear Physics (CHEP 2015), Okinawa, J, April 13-17, 2015 Transparencies publ.online

Beyond HS06: Toward a new HEP CPU benchmark. Update March 2015
Alef, M.; Michelotto, M.
2015. HEPiX Spring 2015 Workshop, Oxford, GB, March 23-27, 2015 Transparencies publ.online

Generalized effective-medium model for the carrier mobility in amorphous organic semiconductors
Rodin, V.; Symalla, F.; Meded, V.; Friederich, P.; Danilov, D.; Poschlad, A.; Nelles, G.; Wrochem, F. von; Wenzel, W.
2015. Physical Review B, 91 (15), Article no: 155203. doi:10.1103/PhysRevB.91.155203

High-level support for simulations in astro- and elementary particle physics
Poghosyan, G.
2015. Physics of particles and nuclei, 45, 804–807. doi:10.1134/S1063779615050226

A Simulation Model for Analysis of Attacks on the Bitcoin Peer-to-Peer Network
Neudecker, T.; Andelfinger, P.; Hartenstein, H.
2015. 1st IEEE/IFIP Workshop on Security for Emerging Distributed Network Technologies (DISSECT), 15th May 2015, Ottawa, Canada. Ed.: R. Badonnel, 1327–1332, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/INM.2015.7140490

Annual cycle and long-term trend of the methane total column in the atmosphere over the St. Petersburg region
Makarova, M. V.; Kirner, O.; Timofeev, Y. M.; Poberovskii, A. V.; Imkhasin, K. K.; Osipov, S. I.; Makarov, B. K.
2015. Izvestiya / Atmospheric and oceanic physics, 51 (4), 431–438. doi:10.1134/S0001433815040088

GASFLOW simulations for cryogenic tank loss of vacuum scenarios
Travis, J. R.; Piccioni Koch, D.
2015. Journal of Energy Challenges and Mechanics, 2 (2), 29–37

GASFLOW analysis for the HySIM hydrogen refueling benchmark
Travis, J. R.; Piccioni Koch, D.
2015. Journal of energy storage, 2, 47–53. doi:10.1016/j.est.2015.06.002

Model-Based Concurrency Analysis of Network Simulations
Andelfinger, P.; Hartenstein, H.
2015. Proceedings of the ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (PADS), London, United Kingdom, Juni 2015, 223–234, Association for Computing Machinery (ACM). doi:10.1145/2769458.2769464

ICON-ART 1.0 - a new online-coupled model system from the global to regional scale
Rieger, D.; Bangert, M.; Bischoff-Gauss, I.; Förstner, J.; Lundgren, K.; Reinert, D.; Schröter, J.; Vogel, H.; Zängl, G.; Ruhnke, R.; Vogel, B.
2015. Geoscientific model development discussions, 8 (1), 567–614. doi:10.5194/gmdd-8-567-2015

Analysis of methane total column variations in the atmosphere near St.Petersburg using ground-based measurements and simulations
Makarova, M. V.; Kirner, O.; Timofeev, Y. M.; Poberovskii, A. V.; Imkhasin, K. K.; Osipov, S. I.; Makarov, B. K.
2015. Izvestiya / Atmospheric and oceanic physics, 51 (2), 177–185. doi:10.1134/S0001433815010089

Partitioning and budget of inorganic and organic chlorine species observed by MIPAS-B and TELIS in the Arctic in March 2011
Wetzel, G.; Oelhaf, H.; Birk, M.; Lange, A. de; Engel, A.; Friedl-Vallon, F.; Kirner, O.; Kleinert, A.; Maucher, G.; Nordmeyer, H.; Orphal, J.; Ruhnke, R.; Sinnhuber, B.-M.; Vogt, P.
2015. Atmospheric chemistry and physics / Discussions, 15 (4), 5391–5422. doi:10.5194/acpd-15-5391-2015

Chlorine nitrate in the atmosphere over St.Petersburg
Virolainen, Y. A.; Timofeyev, Y. M.; Poberovskii, A. V.; Kirner, O.; Hoepfner, M.
2015. Izvestiya / Atmospheric and oceanic physics, 51, 49–56. doi:10.1134/S0001433815010119

High-level support activities of simulation laboratory E&A particles
Poghosyan, G.; Sharma, S.; Kaur, A.; Jindal, V.; Bisht, P.; Streit, A.; Bejger, M.; Krolak, A.; Klaehn, T.; Typjel, S.; Oehlschläger, J.; Pierog, T.; Engel, R.
2015. Nagel, W.E. [Hrsg.] High Performance Computing in Science and Engineering ’14 : Transactions of the High Performance Computing Center, Stuttgart (HLRS), 2014, 121–123, Springer. doi:10.1007/978-3-319-10810-0_9

Future of Monte Carlo simulations of atmospheric showers
Pierog, T.; Engel, R.; Heck, D.; Poghosyan, G.
2015. The European physical journal / Web of Conferences, 89, 01003/1–7. doi:10.1051/epjconf/20158901003

Architecture, implementation and parallization of the software to search for periodic gravitational wave signals
Poghosyan, G.; Matta, S.; Streit, A.; Bejger, M.; Krolak, A.
2015. Computer physics communications, 188, 167–176. doi:10.1016/j.cpc.2014.10.025

Illusion-related brain activations: A new virtual reality mirror box system for use during functional magnetic resonance imaging
Diers, M.; Kamping, S.; Kirsch, P.; Rance, M.; Bekrater-Bodmann, R.; Foell, J.; Trojan, J.; Fuchs, X.; Bach, F.; Maaß, H.; Cakmak, H.; Flor, H.
2015. Brain Research, 1594, 173–182. doi:10.1016/j.brainres.2014.11.001

Quantum dynamical simulation of photoinduced electron transfer processes in dye-semiconductor systems : theory and application to coumarin 343 at TiO₂
Li, J.; Kondov, I.; Wang, H.; Thoss, M.
2015. Journal of physics / Condensed matter, 27 (13), Art. Nr. 134202. doi:10.1088/0953-8984/27/13/134202

Filopodia-based Wnt transport during vertebrate tissue patterning
Stanganello, E.; Hagemann, A. I. H.; Mattes, B.; Sinner, C.; Meyen, D.; Weber, S.; Schug, A.; Raz, E.; Scholpp, S.
2015. Nature Communications, 6, 5846/1–14. doi:10.1038/ncomms6846

The effect of anharmonicities on the atomic dynamics: A molecular dynamics study for liquid sodium
Schmidmeier, K. H.; Brandel, T.; Schommers, W.; Meletis, E.; Politis, C.; Poulopoulos, P.
2015. Quantum Matter, 4, 98–103. doi:10.1166/qm.2015.1176

Chemistry-climate interactions of stratospheric and mesospheric ozone in EMAC long-term simulations with different boundary conditions for CO₂, CH₄, N₂O, and ODS
Kirner, O.; Ruhnke, R.; Sinnhuber, B. M.
2015. Atmosphere-ocean, 53, 140–152. doi:10.1080/07055900.2014.980718

SLA enactment for large-scale healthcare workflows on multi-cloud
Jrad, F.; Tao, J.; Brandic, I.; Streit, A.
2015. Future generation computer systems, 43-44, 135–148. doi:10.1016/j.future.2014.07.005

Confidential database-as-a-service approaches: taxonomy and survey
Köhler, J.; Jünemann, K.; Hartenstein, H.
2015. Journal of Cloud Computing, 4 (1), 1–14. doi:10.1186/s13677-014-0025-1

Contribution of liquid, NAT and ice particles to chlorine activation and ozone depletion in Antarctic winter and spring
Kirner, O.; Müller, R.; Ruhnke, R.; Fischer, H.
2015. Atmospheric Chemistry and Physics, 15 (4), 2019–2030. doi:10.5194/acp-15-2019-2015

An ensemble-averaged, cell density-based digital model of zebrafish embryo development derived from light-sheet microscopy data with single-cell resolution
Kobitski, A. Y.; Otte, J. C.; Takamiya, M.; Schäfer, B.; Mertes, J.; Stegmaier, J.; Rastegar, S.; Rindone, F.; Hartmann, V.; Stotzka, R.; Garcia, A.; Wezel, J. van; Mikut, R.; Strähle, U.; Nienhaus, G. U.
2015. Scientific Reports, 5 (8601), 1–10. doi:10.1038/srep08601

Designing Fail-Safe and Traffic Efficient 802.11p-based Rear-End Collision Avoidance
An, N.; Mittag, J.; Hartenstein, H.
2015. 2014 IEEE Vehicular Networking Conference, VNC 2014; Paderborn; Germany; 3 December 2014 through 5 December 2014, 9–16, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/VNC.2014.7013303

Exploiting the Parallelism of Large-Scale Application-Layer Networks by Adaptive GPU-Based Simulation
Andelfinger, P.; Hartenstein, H.
2015. Proceedings of the 2014 Winter Simulation Conference (WSC’14), December 7 - 10, 2014, Savannah, Georgia, USA. Ed.: A. Tolk, 3471–3482, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/WSC.2014.7020179

Index Optimization for L-Diversified Database-as-a-Service
Köhler, J.; Hartenstein, H.
2015. 9th International Workshop on Data Privacy Management, DPM 2014, 7th International Workshop on Autonomous and Spontaneous Security, SETOP 2014 and 3rd International Workshop on Quantitative Aspects in Security Assurance, QASA 2014 held in conjunction with 19th Annual European Research Event in Computer Security Symposium, ESORICS 2014; Wroclaw; Poland; 10 September 2014 through 11 September 2014. Ed.: J. Posegga, 114–132, Springer. doi:10.1007/978-3-319-17016-9_8

Nonlife ratemaking and risk management with Bayesian generalized additive models for location, scale, and shape
Klein, N.; Denuit, M.; Lang, S.; Kneib, T.
2014. Insurance: Mathematics and Economics, 55, 225–249. doi:10.1016/j.insmatheco.2014.02.001

Bivariate Gaussian Distributional Regression: An Application on Diabetes
Klein, N.; Gude, F.; Cadarso-Suárez, C.; Kneib, T.
2014. Proceedings of the 29th International Workshop on Statistical Modelling. Ed.: T. Kneib. Vol. 1, 167–172, Statistical Modelling Society

Inter-vehicle Communication: Quo Vadis. Report from Dagstuhl Seminar 13392
Dressler, F.; Hartenstein, H.; Altintas, O.; Tonguz, O. (Hrsg.)
2014. Dagstuhl Seminar 13392 - Inter-Vehicular Communication - Quo Vadis. Schloss Dagstuhl, Germany, 22.-25.09.2013, 190–213, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (LZI). doi:10.4230/DagRep.3.9.190

HPC and simulations: Teaching the unteachable? Relaying HPC knowledge at secondary schools - Progress report
Hilpert, J.; Berlich, R.; Lürßen, P.; Zwölfer, A.; Barwind, J.
2014. Proceedings of Science, 210, 036/1–10

Monitoring data streams at process level in scientific big data batch clusters
Kuehn, E.; Fischer, M.; Jung, C.; Petzold, A.; Streit, A.
2014. Proceedings of the International Symposium on Big Data Computing (BDC 2014), London, UK, December 8-9, 2014, 90–952, IEEE Computer Society. doi:10.1109/BDC.2014.21

Status Report of bwFDM-Communities – A State Wide Research Data Management Initiative
Tristram, F.; Wehrle, D.; Cayoglu, U.; Rex, J.; Suchodoletz, D. von
2014. Informatik 2014 - Big Data - Komplexität meistern; 44. Jahrestagung der Gesellschaft für Informatik, Stuttgart, 22.-26. September 2014. Ed.: E. Plödereder, 1669–1673, Ges. für Informatik

Research Data Management within the e-Science Strategy in Baden-Württemberg. Preliminary Results of Project bwFDM-Communities
Cayoglu, U.; Shcherbakov, D.; Tristram, F.
2014. 2nd Data Management Workshop, Köln, 28.-29. November 2014

On the application and performance of MongoDB for climate satellite data
Ameri, P.; Grabowski, U.; Meyer, J.; Streit, A.
2014. Proceedings of the 13th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom 2014), Beijing, CHN, September 24-26, 2014, 652–659, IEEE Computer Society. doi:10.1109/TrustCom.2014.84

The photolysis module JVAL-14, compatible with the MESSy standard, and the JVal PreProcessor (JVPP)
Sander, R.; Jöckel, P.; Kirner, O.; Kunert, A. T.; Landgraf, J.; Pozzer, A.
2014. Geoscientific model development, 7 (6), 2653–2662. doi:10.5194/gmd-7-2653-2014

The Importance of Synchrony and Temporal Order of Visual and Tactile Input for Illusory Limb Ownership Experiences : An fMRI Study Applying Virtual Reality
Bekrater-Bodmann, R.; Foell, J.; Diers, M.; Kamping, S.; Rance, M.; Kirsch, P.; Trojan, J.; Fuchs, X.; Bach, F.; Çakmak, H. K.; Maaß, H.; Flor, H.
2014. PLoS one, 9 (1), Art. Nr. e87013. doi:10.1371/journal.pone.0087013

Highly Selective Dispersion of Single-Walled Carbon Nanotubes via Polymer Wrapping: A Combinatorial Study via Modular Conjugation
Gerstel, P.; Klumpp, S.; Hennrich, F.; Poschlad, A.; Meded, V.; Blasco, E.; Wenzel, W.; Kappes, M. M.; Barner-Kowollik, C.
2014. ACS macro letters, 3 (1), 10–15. doi:10.1021/mz400472q

Selective Dispersion of Large-Diameter Semiconducting Single-Walled Carbon Nanotubes with Pyridine-Containing Copolymers
Berton, N.; Lemasson, F.; Poschlad, A.; Meded, V.; Tristram, F.; Wenzel, W.; Hennrich, F.; Kappes, M. M.; Mayor, M.
2014. Small, 10 (2), 360–367. doi:10.1002/smll.201301295

Native structure-based modeling and simulation of biomolecular systems per mouse click
Lutz, B.; Sinner, C.; Bozic, S.; Kondov, I.; Schug, A.
2014. BMC Bioinformatics, 15 (1), 292/1–12. doi:10.1186/1471-2105-15-292

SLIM: An Improved Generalized Born Implicit Membrane Model
Setzler, J.; Seith, C.; Brieg, M.; Wenzel, W.
2014. Journal of computational chemistry, 35, 2027–2039. doi:10.1002/jcc.23717

Multi-core job support (UGE) at GridKa
Alef, M.
2014. HEPiX Spring 2014 Workshop, Annecy, F, May 19-23, 2014 Transparencies publ.online

GridKa multicore job status
Alef, M.; Hartmann, T.
2014. HEPiX Spring 2014 Workshop, Annecy, F, May 19-23, 2014 Transparencies publ.online

Fast benchmark
Michelotto, M.; Alef, M.
2014. HEPiX Spring 2014 Workshop, Annecy, F, May 19-23, 2014 Transparencies publ.online

HS14 preparation: Current status
Alef, M.; Michelotto, M.
2014. HEPiX Spring 2014 Workshop, Annecy, F, May 19-23, 2014 Transparencies publ.online

Toward a new HEP CPU benchmark. Summary of discussions and remarks
Alef, M.; Michelotto, M.
2014. HEPiX Spring 2014 Workshop, Annecy, F, May 19-23, 2014 Transparencies publ.online

Experiences with Grid engine (UGE) at GridKa
Alef, M.
2014. HEPiX Spring 2014 Workshop, Annecy, F, May 19-23, 2014 Transparencies publ.online

Toward a new HEP CPU benchmark
Alef, M.; Michelotto, M.
2014. HEPiX Spring 2014 Workshop, Annecy, F, May 19-23, 2014 Transparencies publ.online

Beyond HS06: Toward a new HEP CPU benchmark
Alef, M.; Michelotto, M.
2014. HEPiX Spring 2014 Workshop, Annecy, F, May 19-23, 2014 Transparencies publ.online

KIT site report
Alef, M.; Petzold, A.; Schlitter, N.; Weber, P.; Wezel, J. van
2014. HEPiX Spring 2014 Workshop, Annecy, F, May 19-23, 2014 Transparencies publ.online

The GridKa Tier-1 computing center within the ALICE Grid framework
Park, W. J. J.; Jung, C.; Heiss, A.; Petzold, A.; Schwarz, K.
2014. Journal of physics / Conference Series, 513, 062038/1–5. doi:10.1088/1742-6596/513/6/062038

Simulating biomolecular folding and function by native-structure-based/go-type models
Sinner, C.; Lutz, B.; John, S.; Reinartz, I.; Verma, A.; Schug, A.
2014. Israel journal of chemistry, 54, 1165–1175. doi:10.1002/ijch.201400012

Evaluating the performance and scalability of the Ceph distributed storage system
Gudu, D.; Hardt, M.; Streit, A.
2014. Proceedings of the IEEE International Conference on Big Data 2014, Washington, D.C., October 27-30, 2014. Ed.: J. Lin, 177–182, IEEE Computer Society. doi:10.1109/BigData.2014.7004229

Large scale in vivo imaging of the corneal sub-basal nerve plexus by guided eye movements
Allgeier, S.; Köhler, B.; Maier, S.; Peschel, S.; Reichert, K. M.; Stachs, O.; Wezel, J. van; Mikut, R.; Bretthauer, G.
2014. Biomedizinische Technik, 59 (s1), s572

Impact of acetone (photo)oxidation on HOx production in the UT/LMS based on CARIBIC passenger aircraft observations and EMAC simulations
Neumaier, M.; Ruhnke, R.; Kirner, O.; Ziereis, H.; Stratmann, G.; Brenninkmeijer, C. A. M.; Zahn, A.
2014. Geophysical research letters, 41, 3289–3297. doi:10.1002/2014GL059480

Radiative and dynamical contributions to past and future Arctic stratospheric temperature trends
Bohlinger, P.; Sinnhuber, B. M.; Ruhnke, R.; Kirner, O.
2014. Atmospheric chemistry and physics, 14, 1679–1688. doi:10.5194/acp-14-1679-2014

Electron-vibration interaction in the presence of a switchable Kondo resonance realized in a molecular junction
Rakhmilevitch, D.; Korytar, R.; Bagrets, A.; Evers, F.; Tal, O.
2014. Physical review letters, 113, 236603/1–6. doi:10.1103/PhysRevLett.113.236603

Device-driven metadata management solutions for scientific big data use cases
Grunzke, R.; Müller-Pfefferkorn, R.; Jäkel, R.; Starek, J.; Hardt, M.; Hartmann, V.; Potthoff, J.; Hesser, J.; Kepper, N.; Hausmann, M.; Gesing, S.; Kindermann, S.
2014. Proceedings of the 22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, Torino, I, February 12-14, 2014, 317–321, IEEE Computer Society. doi:10.1109/PDP.2014.119

Multiscale simulations in organic electronics: Applications to polymer wrapping of single-walled carbon nanotubes, bulk charge mobilities and organic-organic interfaces. Dissertation
Poschlad, A.
2014. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000044652

Integration of eSBMTools into the MoSGRID portal using the gUSE technology
Bozic, S.; Krüger, J.; Sinner, C.; Lutz, B.; Schug, A.; Kondov, I.
2014. Proceedings of the 6th International Workshop on Science Gateways (IWSG 2014), Dublin, IRL, June 3-5, 2014, 85–90, IEEE Computer Society. doi:10.1109/IWSG.2014.21

An EMF-based toolkit for creation of domain-specific data services
Bender, A.; Bozic, S.; Kondov, I.
2014. 2nd International Conference on Model-Driven Engineering and Software Development (MODELSWARD 2014), Lisboa, P, January 7-9, 2014, 30–40, SciTePress. doi:10.5220/0004701900300040

An Implicit Solvent Model for Biomolecular Monte Carlo Simulations. Dissertation
Brieg, M.
2014. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000044641

On Spatial Measures for Geotagged Social Media Contents
Wang, X.; Gaugel, T.; Keller, M.
2014. 5th International Workshop on Mining Ubiquitous and Social Environments, Nancy, France, September 15th, 2014

Appropriate Selection of Urban Vehicle-to-Vehicle Radio Propagation Models
Gaugel, T.; Hartenstein, H.
2014. 2014 21st IEEE Symposium on Communications and Vehicular Technology in the BeNeLux, IEEE SCVT 2014; Delft; Netherlands; 10 November 2014 through, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SCVT.2014.7046698

Using a vision cognitive algorithm to schedule virtual machines
Zhao, J.; Mhedheb, Y.; Tao, J.; Jrad, F.; Liu, Q.; Streit, A.
2014. International journal of applied mathematics and computer science, 24, 535–550. doi:10.2478/amcs-2014-0039

A security framework in G-Hadoop for big data computing across distributed Cloud data centres
Zhao, J.; Wang, L.; Tao, J.; Chen, J.; Sun, W.; Ranjan, R.; Kolodziej, J.; Streit, A.; Georgakopoulos, D.
2014. Journal of computer and system sciences, 80, 994–1007. doi:10.1016/j.jcss.2014.02.006

Management of meteorological mass data with MongoDB
Lutz, R.; Ameri, P.; Latzko, T.; Meyer, J.
2014. Proceedings of the 28th International Conference on Informatics for Environmental Protection (ENVIROINFO 2014), Oldenburg, September 10-12, 2014. Hrsg.: J. M. Gomez, 549–556, Verlag BIAS

Real-time Response Framework Using MongoDB and 3D Visualisation
Ameri, P.; Szuba, M.
2014. Large-Scale Data Management and Analysis (LSDMA) - Big Data in Science. Hrsg.: Ch. Jung, 28–29, Karlsruher Institut für Technologie (KIT)

Federated AAI: Enabling Collaboration
Millar, P.; Fuhrmann, patrick; Klein, D.; Hayrapetyan, A.; Hardt, M.
2014. Large-Scale Data Management and Analysis (LSDMA) - Big Data in Science. Hrsg.: Ch. Jung, 24–26, Karlsruher Institut für Technologie (KIT)

Editorial
Streit, A.
2014. Large-Scale Data Management and Analysis (LSDMA) - Big Data in Science. Hrsg.: Ch. Jung, 3, Karlsruher Institut für Technologie (KIT)

Large-Scale Data Management and Analysis (LSDMA) - Big Data in Science
Jung, C.; Streit, A. (Hrsg.)
2014. Karlsruher Institut für Technologie (KIT)

Efficient calculation of rate constants: Downhill versus uphill sampling
Klenin, K. V.
2014. The journal of chemical physics, 141, 074103/1–6. doi:10.1063/1.4892565

GASFLOW simulations of a bonfire test
Travis, J. R.; Piccioni Koch, D.
2014. International journal of hydrogen energy, 39, 13041–13047. doi:10.1016/j.ijhydene.2014.06.026

Inter-vehicle Communication: Quo Vadis
Dressler, F.; Hartenstein, H.; Altintas, O.; Tonguz, O.
2014. IEEE communications magazine, 52 (6), 170–177. doi:10.1109/MCOM.2014.6829960

Featured "Single Sign-in" interface enabling Grid, cloud and local resources for HEP
Fischer, M.; Quast, G.; Zvada, M.
2014. Journal of physics / Conference Series, 513, Art.Nr. 032033. doi:10.1088/1742-6596/513/3/032033

Contribution of liquid, NAT and ice particles to chlorine activation and ozone depletion during Antarctic winter and spring
Kirner, O.; Müller, R.; Ruhnke, R.; Fischer, H.
2014. Atmospheric chemistry and physics / Discussions, 14 (10), 14833–14854. doi:10.5194/acpd-14-14833-2014

Preparing the electrical data recorder for comparative power network measurements
Maass, H.; Cakmak, H. K.; Bach, F.; Kühnapfel, U. G.
2014. Proceedings of IEEE International Energy Conference (EnergyCon 2014), Dubrovnik, HR, May 13-16, 2014, 759–765, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ENERGYCON.2014.6850511

Fast Segmentation of Stained Nuclei in Terabyte-Scale, Time Resolved 3D Microscopy Image Stacks
Stegmaier, J.; Otte, J. C.; Kobitski, A.; Bartschat, A.; Garcia, A.; Nienhaus, G. U.; Strähle, U.; Mikut, R.
2014. PLoS ONE, 9 (2), e90036/1–11. doi:10.1371/journal.pone.0090036

Optimization of data life cycles
Jung, C.; Gasthuber, M.; Giesler, A.; Hardt, M.; Meyer, J.; Rigoll, F.; Schwarz, K.; Stotzka, R.; Streit, A.
2014. Journal of physics / Conference Series, 513 (TRACK 3), Art. Nr.: 032047. doi:10.1088/1742-6596/513/3/032047

Archival services and technologies for scientific data
Meyer, J.; Hardt, M.; Streit, A.; Wezel, J. van
2014. Journal of physics / Conference Series, 513, 062033/1–6. doi:10.1088/1742-6596/513/6/062033

FOSP: Towards a Federated Object Sharing Protocol that Unifies Operartions on Social Content
Maurer, F.; Labitzke, S.
2014. 7. DFN-Forum Kommunikationstechnologien : Beiträge der Fachtagung 16.06. - 17.06.2014 Fulda. Hrsg.: P. Müller [Konferenz], 57–66, Köllen Druck+Verlag

Anforderungen eines nachhaltigen, disziplinübergreifenden Forschungsdaten-Repositoriums
Potthoff, J.; Van Wezel, J.; Razum, M.; Walk, M.
2014. 7. DFN-Forum Kommunikationstechnologien : Beiträge der Fachtagung 16.06. - 17.06.2014 Fulda. Hrsg.: P. Müller, 11–20, Köllen Druck+Verlag

HS4MC : Hierarchical SLA-based service selection for multi-Cloud environments
Farokhi, S.; Jrad, F.; Brandic, I.; Streit, A.
2014. 4th International Conference on Cloud Computing and Services Science (CLOSER 2014), Barcelona, E, April 3-5, 2014, 722–734, SciTePress

Storage CloudSim : A simulation environment for cloud object storage infrastructures
Sturm, T.; Jrad, F.; Streit, A.
2014. 4th International Conference on Cloud Computing and Services Science (CLOSER 2014), Barcelona, E, April 3-5, 2014 Proceedings , 2014, 186–192, SciTePress

Multi-dimensional resource allocation for data-intensive large-scale cloud applications
Jrad, F.; Tao, J.; Brandic, I.; Streit, A.
2014. 4th International Conference on Cloud Computing and Services Science (CLOSER 2014), Barcelona, E, April 3-5, 2014, 691–702, SciTePress

Understanding differences in MAC performance
Gaugel, T.; Mittag, J.; Hartenstein, H.; Ström, E.
2014. Proceeding of 15th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, WoWMoM 2014; Sydney; Australia; 19 June 2014 through, Art. Nr.: 6918995, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/WoWMoM.2014.6918995

FOSP: Towards a Federated Object Sharing Protocol that Unifies Operations on Social Content
Maurer, F.; Labitzke, S.
2014. 7. DFN-Forum Kommunikationstechnologien - 7th DFN Forum on Communication Technologies; Fulda; Germany; 16 June 2014 through 17 June 2014, 57–66, Gesellschaft für Informatik (GI)

Self-Optimization of DHT Lookups through Run-Time Performance Analysis
Jünemann, K.; Hartenstein, H.
2014. Proceedings of the 2014 International Conference on High Performance Computing and Simulation, HPCS 2014; Bologna; Italy; 21 July 2014 through 25 July 2014, 407–415, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/HPCSim.2014.6903714

SECURUS: Composition of Confidentiality Preserving Indexing Approaches for Secure Database-as-a-Service
Köhler, J.; Jünemann, K.; Hartenstein, H.
2014. Praxis der Informationsverarbeitung und Kommunikation, 37 (2), 149–155. doi:10.1515/pik-2014-0011

Technologies - Communication: Wireless LAN-Based Vehicular Communication
Festag, A.; Hartenstein, H.; Mittag, J.
2014. Encyclopedia of Automotive Engineering, online, John Wiley and Sons. doi:10.1002/9781118354179.auto170

Securus: From Confidentiality and Access Requirements to Data Outsourcing Solutions
Köhler, J.; Jünemann, K.
2014. Privacy and Identity Management for Emerging Services and Technologies : 8th IFIP WG 9.2, 9.5, 9.6/11.7, 11.4, 11.6 International Summer School, Nijmegen, The Netherlands, June 17-21, 2013. [Konferenz]. Ed.: M. Hansen, 139–149, Springer-Verlag

Evaluation of wind energy potential over Thailand by using an atmospheric mesoscale model and a GIS approach
Janjai, S.; Masiri, I.; Promsen, W.; Pattarapanitchai, S.; Pankaew, P.; Laksanaboonsong, J.; Bischoff-Gauss, I.; Kalthoff, N.
2014. Journal of wind engineering and industrial aerodynamics, 129, 1–10. doi:10.1016/j.jweia.2014.03.010

Combining the X.509 and the SAML Federated Identity Management Systems
Hardt, M.; Hayrapetyan, A.; Millar, P.; Memon, S.
2014. Recent Trends in Computer Networks and Distributed Systems Security : 2nd International Conference, SNDS 2014, Trivandrum, IND, 13.03.-14.03.2014. Hrsg.: G. Martinez Perez, 404–415, Springer-Verlag

Differences between cotranscriptional and free riboswitch folding
Lutz, B.; Faber, M.; Verma, A.; Klumpp, S.; Schug, A.
2014. Nucleic Acids Research, 42 (4), 2687–2696. doi:10.1093/nar/gkt1213

Hochleistungsrechnen in Baden-Württemberg - Ausgewählte Aktivitäten im bwGRiD 2012 : Beiträge zu Anwenderprojekten und Infrastruktur im bwGRiD im Jahr 2012
Schulz, J. C.; Hermann, S. (Hrsg.)
2014. KIT Scientific Publishing. doi:10.5445/KSP/1000039516

bwIDM - Federated Access to IT-Based Services at the Universities of the State of Baden-Württemberg
Köhler, J.; Labitzke, S.; Simon, M.; Dussa, T.; Nussbaumer, M.; Hartenstein, H.
2014. Praxis der Informationsverarbeitung und Kommunikation, 37 (1), 15–21. doi:10.1515/pik-2013-0025

Parallelism Potentials in Distributed Simulations of Kademlia-Based Peer-to-Peer Networks
Andelfinger, P.; Jünemann, K.; Hartenstein, H.
2014. Proceedings of the 7th International Conference on Simulation Tools and Techniques, SIMUTools 2014; Lisbon; Portugal; 17 March 2014 through 19 March 2014. Ed.: R. Roland, 41–50, ICST. doi:10.4108/icst.simutools.2014.254609

From Implicit to Explicit Knowledge: A Tool for Preserving and Sharing Mental Links in Science
Andelfinger, P.; Keller, M.; Kühner, H.; Hartenstein, H.
2014. Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW 2014), Baltimore, Maryland, USA, 15-19 Februar 2014, 129–132, Association for Computing Machinery (ACM). doi:10.1145/2556420.2556476

Novel series connection concept for thin film solar modules : Novel series connection concept for thin film solar modules
Haas, S.; Krumscheid, S.; Bauer, A.; Lambertz, A.; Rau, U.
2013. Progress in Photovoltaics: Research and Applications, 21 (5), 972–979. doi:10.1002/pip.2188

Bayesian Generalized Additive Models for Location, Scale and Shape for Insurance Data
Klein, N.; Kneib, T.; Lang, S.
2013. Proceedings of the 28th International Workshop on Statistical Modelling. Ed.: V.M.R. Muggeo. Vol. 2, 645–650, Statistical Modelling Society

Semiparametric Drift and Diffusion Estimation for Multiscale Diffusions
Krumscheid, S.; Pavliotis, G. A.; Kalliadasis, S.
2013. Multiscale Modeling & Simulation, 11 (2), 442–473. doi:10.1137/110854485

Algebraic reconstruction of ultrafast tomography images at the large scale data facility
Yang, X.; Jejkal, T.; Stotzka, R.; Pasic, H.; Santos Rolo, T. dos; Kamp, T. van de; Streit, A.
2013. 14th International Conference on Accelerator & Large Experimental Physics Control Systems (ICALEPCS2013), San Francisco, CA, October 6-11, 2013, 996–999, NIF/LLNL

Data intensive computing of X-ray computed tomography reconstruction at the LSDF
Yang, X.; Jejkal, T.; Pasic, H.; Stotzka, R.; Streit, A.; Wezel, J. van; Santos Rolo, T. dos
2013. Proceedings of the 21st International Euromicro Conference on Parallel, Distributed and Network-based Processing (PDP 2013), Belfast, GB, February 27 - March 1, 2013. Ed.: P. Kilpatrick, 86–93, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PDP.2013.21

Calculation of the "absolute" free energy of a ß-hairpin in an all-atom force field
Klenin, K. V.; Wenzel, W.
2013. The journal of chemical physics, 139 (5), Art.Nr. 054102. doi:10.1063/1.4817195

Triple-S: A Matching Approach for Petri Nets on Syntactic, Semantic and Structural level
Cayoglu, U.; Oberweis, A.; Schoknecht, A.; Ullrich, M.
2013. Model Matching Contest at the 4th International Workshop on Process Model Collections: Management and Reuse (PMC-MR’13) in conjunction with the 11th International Conference on Business Process Management, Beijing, China, August 26, 2013

Radiative and dynamical contributions to past and future Arctic stratospheric temperature trends
Bohlinger, P.; Sinnhuber, B.-M.; Ruhnke, R.; Kirner, O.
2013. Atmospheric chemistry and physics / Discussions, 13 (3), 6707–6728. doi:10.5194/acpd-13-6707-2013

G-Hadoop : MapReduce across distributed data centers for data-intensive computing
Wang, L.; Tao, J.; Ranjan, R.; Marten, H.; Streit, A.; Chen, J.; Chen, D.
2013. Future generation computer systems, 29 (3), 739–750. doi:10.1016/j.future.2012.09.001

The Influence of Energetic Particles on the Chemistry of the Middle Atmosphere
Reddmann, T.; Funke, B.; Konopka, P.; Stiller, G.; Versick, S.; Vogel, B.
2013. Climate and Weather of the Sun-Earth System (CAWSES) Highlights from a Priority Program. Ed.: F.-J. Lübken, 247–273, Springer-Verlag. doi:10.1007/978-94-007-4348-9_15

Special Section on Vehicular Networks and Communication Systems: From Laboratory into Reality
Bai, F.; Hartenstein, H.; Gruteser, M.; Kravets, R.; Zhang, T.; Stancil, D.
2013. IEEE transactions on vehicular technology, 62 (9), 4146–4149. doi:10.1109/TVT.2013.2286434

In-depth Analysis and Evaluation of Self-Organizing TDMA
Gaugel, T.; Mittag, J.; Hartenstein, H.; Papanastasiou, S.; Ström, E.
2013. Proceedings of the 2013 IEEE Vehicular Networking Conference, VNC 2013; Boston, MA; United States; 16 December 2013 through 18 December 2013, 79–86, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/VNC.2013.6737593

Verification and Evaluation of Fail-Safe Virtual Traffic Light Applications
Neudecker, T.; An, N.; Hartenstein, H.
2013. Proceedings of the 2013 IEEE Vehicular Networking Conference, VNC 2013; Boston, MA; United States; 16 December 2013 through 18 December 2013, 158–165, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/VNC.2013.6737603

eID im Forschungsprozess
Johannes, P. C.; Roßnagel, A.; Potthoff, J.; Neumair, B.; Madiesh, M.; Hackel, S.
2013. Informationssicherheit stärken - Vertrauen in die Zukunft schaffen: Tagungsband zum 13.Deutschen IT-Sicherheitskongress, Bonn, 14.-16. Mai 2013. Hrsg.: M. Hange, 405–418, SecuMedia-Verlag

Beweissicheres elektronisches Laborbuch : Anforderungen, Konzepte und Umsetzung zur langfristigen, beweiswerterhaltenden Archivierung elektronischer Forschungsdaten und -dokumentation
Johannes, P. C.; Potthoff, J.; Roßnagel, A.; Neumair, B.; Madiesh, M.; Hackel, S.
2013. Baden-Baden : Nomos Verl., 2013 (Der elektronische Rechtsverkehr ; 29)

An augmented reality home-training system based on the mirror training and imagery approach
Trojan, J.; Diers, M.; Fuchs, X.; Bach, F.; Bekrater-Bodmann, R.; Foell, J.; Kamping, S.; Rance, M.; Maaß, H.; Flor, H.
2013. Behavior research methods, 46 (3), 634–640. doi:10.3758/s13428-013-0412-4

Using Traditional data analysis algorithms to detect patterns for big data processing
Zhao, J.; Tao, J.; Wang, L.; Ranjan, R.; Kolodziej, J.
2013. IEEE International Conference on High Performance Computing and Communications, Zhangjiajie, China, November 13-15, 2013 Proceedings S.1097-1104 Los Alamitos, Calif. : IEEE Computer Society, 2013 S.1097-1104

Load and thermal-aware VM scheduling on the cloud
Mhedheb, Y.; Jrad, F.; Tao, J.; Zhao, J.; Kolodziej, J.; Streit, A.
2013. Algorithms and Architectures for Parallel Processing: 13th International Conference, Vietri sul Mare, I, December 18-20, 2013. Hrsg.: J. Kolodziej. Pt. 1, 101–114, Springer-Verlag. doi:10.1007/978-3-319-03859-9_8

Transport properties of individual C₆₀-molecules
Geranton, G.; Seiler, C.; Bagrets, A.; Venkataraman, L.; Evers, F.
2013. Journal of Chemical Physics, 139, 234701/1–12. doi:10.1063/1.4840535

One year high rate low voltage recording. Devices, methods and results
Maaß, H.; Cakmak, H. K.; Bach, F.; Kühnapfel, U. G.
2013. 4th IEEE International Workshop on Applied Measurements for Power Systems (AMPS), Aachen, 25.-27. September 2013, 68–72, Institute of Electrical and Electronics Engineers (IEEE)

Multiscale modelling methods for applications in materials science
Kondov, I.; Sutmann, G. (Hrsg.)
2013. Forschungszentrum Jülich

Metadaten - Welche Informationen sind wichtig? Proseminar - Big Data Applications
Turan, M.
2013. Seminar Big Data Applications. Sammelband. Sommersemester 2013. Hrsg.: A. Streit, III, 10 S., Karlsruher Institut für Technologie (KIT)

Langzeitarchivierung von Big Forschungsdaten, Proseminar "Big Data"
Mayer, A.
2013. Seminar Big Data Applications. Sammelband. Sommersemester 2013. Hrsg.: A. Streit, 18 S., Karlsruher Institut für Technologie (KIT)

Schafft Replikation Sicherheit? Kosten vs. Nutzen. Proseminar "BigData", Sommersemester 2013
Markert, J.-F.
2013. Seminar Big Data Applications. Sammelband. Sommersemester 2013. Hrsg.: A. Streit, 11 S., Karlsruher Institut für Technologie (KIT)

Bitstream Preservation: Verfahren und Algorithmen. Proseminar-Ausarbeitung
Sauter, D.
2013. Seminar Big Data Applications. Sammelband. Sommersemester 2013. Hrsg.: A. Streit, III, 16 S., Karlsruher Institut für Technologie (KIT)

Digitalisierungs- und Bereitstellungsprojekte in Deutschland. Seminararbeit Big Data Applications
Cömert, M.
2013. Seminar Big Data Applications. Sammelband. Sommersemester 2013. Hrsg.: A. Streit, 18 S., Karlsruher Institut für Technologie (KIT)

Seminar Big Data Applications. Sammelband. Sommersemester 2013
Streit, A.; Stotzka, R. (Hrsg.)
2013. Karlsruher Institut für Technologie (KIT)

Avoiding Unintended Flows of Personally Identifiable Information - Enterprise Identity Management and Online Social Networks. Dissertation
Labitzke, S.
2013. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000036761

A toolchain for profiling virtual machines
Zhao, J.; Tao, J.; Wang, L.; Wirooks, A.
2013. Rekdalsbakken, W. [Hrsg.] Proceedings of the 27th European Conference on Modelling and Simulation, Aalesund, N, May 27-30, 2013 European Council for Modelling and Simulation, 2013

A service-oriented framework for integration of domain-specific data models in scientific workflows
Bender, A.; Poschlad, A.; Bozic, S.; Kondov, I.
2013. Procedia Computer Science, 18, 1087–1097. doi:10.1016/j.procs.2013.05.274