Dr. Markus Götz
- Gruppenleiter Helmholtz AI Consultants Energy
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449
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329
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+49 721 608-29334
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markus goetz ∂does-not-exist.kit edu
- 01/2018 –
Wissenschaftlicher Mitarbeiter Scientific Computing Center (SCC), Karlsruher Institut für Technologie (KIT) - 04/2014 – 12/2017
Promotion in Computational Engineering, School of Engineering and Natural Sciences (SENS), Universität Island und Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich (FZJ) - 09/2010 – 03/2014
Master of Science in IT-System Engineering, Hasso-Plattner-Institut (HPI), Universität Potsdam - 06/2011 – 09/2011
Europäische Organisation für Kernforschung (CERN), Genf, Schweiz - 08/2010 – 06/2011
ERASMUS Blekinge Tekniska Högskola (BTH), Karlskrona, Schweden - 09/2007 – 07/2010
Bachelor of Science in IT-Systems Engineering, Hasso-Plattner-Institut (HPI), Universität Potsdam
Publikationsliste KITopen
Exploring Federated Learning for Thermal Urban Feature Segmentation - A Comparison of Centralized and Decentralized Approaches
Duda, L.; Alibabaei, K.; Vollmer, E.; Klug, L.; Kozlov, V.; Berberi, L.; Benz, M.; Volk, R.; Gutiérrez Hermosillo Muriedas, J. P.; Götz, M.; Sáinz-Pardo Díaz, J.; López García, Á.; Schultmann, F.; Streit, A.
2025. Computational Science and Its Applications – ICCSA 2025 : 25th International Conference, Istanbul, Turkey, June 30 – July 3, 2025, Proceedings, Part I. Ed.: O. Gervasi, 285–302, Springer Nature Switzerland. doi:10.1007/978-3-031-97000-9_18
Duda, L.; Alibabaei, K.; Vollmer, E.; Klug, L.; Kozlov, V.; Berberi, L.; Benz, M.; Volk, R.; Gutiérrez Hermosillo Muriedas, J. P.; Götz, M.; Sáinz-Pardo Díaz, J.; López García, Á.; Schultmann, F.; Streit, A.
2025. Computational Science and Its Applications – ICCSA 2025 : 25th International Conference, Istanbul, Turkey, June 30 – July 3, 2025, Proceedings, Part I. Ed.: O. Gervasi, 285–302, Springer Nature Switzerland. doi:10.1007/978-3-031-97000-9_18
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
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
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
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
Enhancing UAS-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
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
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
Schumacher, M.; Götz, M.; Dederer, G.; Lee, M.
2024. Journal of applied hydrography = Hydrographische Nachrichten, 127 (3), 20–25. doi:10.23784/HN127-04
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
Laufer, F.; Götz, M.; Paetzold, U. W.
2025. Energy & Environmental Science. doi:10.1039/D4EE03445G
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
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
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
Gazos, A.; Kahn, J.; Kusche, I.; Büscher, C.; Götz, M.
2025. Safety Science, 184, 106731. doi:10.1016/j.ssci.2024.106731
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
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
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
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
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
Comparative Study of Federated Learning Frameworks NVFlare and Flower for Detecting Thermal Bridges in Urban Environments
Duda, L. J.; Alibabaei, K. F.; Vollmer, E.; Klug, L.; Benz, M.; Kozlov, V.; Rebekka Volk; Götz, M.; Schultmann, F.; Streit, A.
2024, September 3. EGI Conference (2024), Lecce, Italien, 30. September–4. Oktober 2024
Duda, L. J.; Alibabaei, K. F.; Vollmer, E.; Klug, L.; Benz, M.; Kozlov, V.; Rebekka Volk; Götz, M.; Schultmann, F.; Streit, A.
2024, September 3. EGI Conference (2024), Lecce, Italien, 30. September–4. Oktober 2024
Thermal Bridges on Building Rooftops - Hyperspectral (RGB + Thermal + Height) drone images of Karlsruhe, Germany, with thermal bridge annotations
Mayer, Z.; Kahn, J.; Hou, Y.; Beiersdörfer, T.; Blumenröhr, N.; Götz, M.; Volk, R.
2022, August 25. doi:10.5281/zenodo.7022736
Mayer, Z.; Kahn, J.; Hou, Y.; Beiersdörfer, T.; Blumenröhr, N.; Götz, M.; Volk, R.
2022, August 25. doi:10.5281/zenodo.7022736
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
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
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
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
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
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
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
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
(Semi-) Automatic Review Process for Common Compound Characterization Data in Organic Synthesis
Huang, Y.-C.; Tremouilhac, P.; Kuhn, S.; Huang, P.-C.; Lin, C.-L.; Schlörer, N.; Taubert, O.; Götz, M.; Jung, N.; Bräse, S.
2024. ChemRxiv. doi:10.26434/chemrxiv-2024-1r9tb
Huang, Y.-C.; Tremouilhac, P.; Kuhn, S.; Huang, P.-C.; Lin, C.-L.; Schlörer, N.; Taubert, O.; Götz, M.; Jung, N.; Bräse, S.
2024. ChemRxiv. doi:10.26434/chemrxiv-2024-1r9tb
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
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
Surrogate Modelling for Core Degradation in pressurized Water Reactors
Dressner, J.; Götz, M.; Stakhanova, A.; Gabrielli, F.; Debus, C.
2024. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2024), Düsseldorf, Deutschland, 12.–14. Juni 2024
Dressner, J.; Götz, M.; Stakhanova, A.; Gabrielli, F.; Debus, C.
2024. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2024), Düsseldorf, Deutschland, 12.–14. Juni 2024
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
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
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
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
How Does Feature Engineering Impact UAV-based Multispectral Semantic Segmentation? An RGB and Thermal Image Ablation Study
Vollmer, E.; Benz, M.; Kahn, J.; Klug, L.; Volk, R.; Schultmann, F.; Götz, M.
2024, Juni 12. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2024), Düsseldorf, Deutschland, 12.–14. Juni 2024
Vollmer, E.; Benz, M.; Kahn, J.; Klug, L.; Volk, R.; Schultmann, F.; Götz, M.
2024, Juni 12. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2024), Düsseldorf, Deutschland, 12.–14. Juni 2024
Simulation and Data Life Cycle Labs at SCC
Aversa, R.; Azmi, E.; Fischer, M.; Götz, M.
2024, Mai 2. Strategic Advisory Board (SAB) meeting for the Helmholtz Program EDF (2024), Karlsruhe, Deutschland, 2. Mai 2024
Aversa, R.; Azmi, E.; Fischer, M.; Götz, M.
2024, Mai 2. Strategic Advisory Board (SAB) meeting for the Helmholtz Program EDF (2024), Karlsruhe, Deutschland, 2. Mai 2024
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
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
Understanding Scalable Perovskite Solar Cell Manufacturing with Explainable AI
Klein, L.; Ziegler, S.; Laufer, F.; Debus, C.; Götz, M.; Maier-Hein, K.; Paetzold, U.; Isensee, F.; Jaeger, P.
2023
Klein, L.; Ziegler, S.; Laufer, F.; Debus, C.; Götz, M.; Maier-Hein, K.; Paetzold, U.; Isensee, F.; Jaeger, P.
2023
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
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
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
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
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
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
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. doi:10.48550/arXiv.2301.08713
Taubert, O.; Weiel, M.; Coquelin, D.; Farshian, A.; Debus, C.; Schug, A.; Streit, A.; Götz, M.
2023. doi:10.48550/arXiv.2301.08713
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
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
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
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
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
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
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
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
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
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
Lowest Common Ancestor Generations (LCAG) Phasespace Particle Decay Reconstruction Dataset
Kahn, J.; Taubert, O.; Tsaklidis, I.; Reuter, L.; Dujany, G.; Boeckh, T.; Thaller, A.; Goldenzweig, P.; Bernlochner, F.; Streit, A.; Götz, M.
2022, August 11. doi:10.5281/zenodo.6983258
Kahn, J.; Taubert, O.; Tsaklidis, I.; Reuter, L.; Dujany, G.; Boeckh, T.; Thaller, A.; Goldenzweig, P.; Bernlochner, F.; Streit, A.; Götz, M.
2022, August 11. doi:10.5281/zenodo.6983258
Hyperspectral (RGB + Thermal) drone images of Karlsruhe, Germany - Raw images for the Thermal Bridges on Building Rooftops (TBBR) dataset
Kahn, J.; Mayer, Z.; Hou, Y.; Beiersdörfer, T.; Götz, M.; Volk, R.
2022, November 25. doi:10.5281/zenodo.7360996
Kahn, J.; Mayer, Z.; Hou, Y.; Beiersdörfer, T.; Götz, M.; Volk, R.
2022, November 25. doi:10.5281/zenodo.7360996
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
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
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
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
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
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
Thermal Bridges on Building Rooftops - Hyperspectral (RGB + Thermal + Height) drone images of Karlsruhe, Germany, with thermal bridge annotations
Mayer, Z.; Kahn, J.; Hou, Y.; Beiersdörfer, T.; Götz, M.; Volk, R.
2022, Mai 11. doi:10.5281/zenodo.6517768
Mayer, Z.; Kahn, J.; Hou, Y.; Beiersdörfer, T.; Götz, M.; Volk, R.
2022, Mai 11. doi:10.5281/zenodo.6517768
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
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
Heat - A Distributed and Accelerated Tensor Framework for Data Analytics and Machine Learning
Comito, C.; Götz, M.; Debus, C.; Coquelin, D.; Tarnawa, M.; Krajsek, K.; Knechtges, P.; Siggel, M.; Hagemeier, B.; Basermann, A.; Streit, A.
2021, Oktober 5. 1st Artificial Intelligence Symposium on Theory, Application & Research (AI STAR 2021), Online, 5.–6. Oktober 2021
Comito, C.; Götz, M.; Debus, C.; Coquelin, D.; Tarnawa, M.; Krajsek, K.; Knechtges, P.; Siggel, M.; Hagemeier, B.; Basermann, A.; Streit, A.
2021, Oktober 5. 1st Artificial Intelligence Symposium on Theory, Application & Research (AI STAR 2021), Online, 5.–6. Oktober 2021
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
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
A Computational Workflow for Interdisciplinary Deep Learning Projects utilizing bwHPC Infrastructure
Schilling, M. P.; Neumann, O.; Scherr, T.; Cui, H.; Popova, A. A.; Levkin, P. A.; Götz, M.; Reischl, M.
2021, November 8. 7th bwHPC Symposium (2021), Online, 8. November 2021
Schilling, M. P.; Neumann, O.; Scherr, T.; Cui, H.; Popova, A. A.; Levkin, P. A.; Götz, M.; Reischl, M.
2021, November 8. 7th bwHPC Symposium (2021), Online, 8. November 2021
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.
2021. Springer. doi:10.21203/rs.3.rs-832355/v1
Coquelin, D.; Debus, C.; Götz, M.; Lehr, F. von der; Kahn, J.; Siggel, M.; Streit, A.
2021. Springer. doi:10.21203/rs.3.rs-832355/v1
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
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
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
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
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
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)
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)
HeAT – a Distributed and GPU-accelerated Tensor Framework for Data Analytics
Götz, M.; Coquelin, D.; Debus, C.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. doi:10.5445/IR/1000123473
Götz, M.; Coquelin, D.; Debus, C.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. doi:10.5445/IR/1000123473
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
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
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
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
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
Krajsek, K.; Comito, C.; Götz, M.; Hagemeier, B.; Knechtges, P.; Siggel, M.
2018. Proceedings of the Extreme Data Workshop 2018
Machine learning-aided numerical linear algebra: Convolutional neural network for the efficient preconditioner generation
Götz, M.; Anzt, H.
2018. ScalA18: 9th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Dallas, TX, November 12, 2018
Götz, M.; Anzt, H.
2018. ScalA18: 9th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Dallas, TX, November 12, 2018
Abschlussarbeiten
Motivierte Studierende können sich aus einer Reihe von Bachelor- und Masterarbeitsthemen in den Themenbereichen: künstlicher Intelligenz, Hochleistungsrechnen und Anwendungen in der Energieinformatik wählen.
Weitere Informationen können per E-Mail erfragt werden.
- 2019 –
Helmholtz Artificial Intelligence Cooperation Unit (Helmholtz AI) - 2020 –
Protein Folding by Learning (ProFiLe) - 2017 – 2021
Helmholtz Analytics Framework (HAF) - 2012 – 2016
Large-Scale Data Management and Analysis (LSDMA)