| HPDBSCAN: highly parallel DBSCAN M Götz, C Bodenstein, M Riedel Proceedings of the workshop on machine learning in high-performance …, 2015 | 75 | 2015 |
| Dynamic particle swarm optimization of biomolecular simulation parameters with flexible objective functions M Weiel, M Götz, A Klein, D Coquelin, R Floca, A Schug Nature Machine Intelligence 3 (8), 727-734, 2021 | 33 | 2021 |
| Machine Learning-Aided Numerical Linear Algebra: Convolutional Neural Networks for the Efficient Preconditioner Generation M Götz, H Anzt 2018 IEEE/ACM 9th Workshop on Latest Advances in Scalable Algorithms for …, 2018 | 31 | 2018 |
| The Influence of Sampling Methods on Pixel-Wise Hyperspectral Image Classification with 3D Convolutional Neural Networks J Lange, G Cavallaro, M Götz, E Erlingsson, M Riedel IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium …, 2018 | 28 | 2018 |
| Parallel computation of component trees on distributed memory machines M Götz, G Cavallaro, T Géraud, M Book, M Riedel IEEE transactions on parallel and distributed systems 29 (11), 2582-2598, 2018 | 25 | 2018 |
| Smart data analytics methods for remote sensing applications G Cavallaro, M Riedel, JA Benediktsson, M Goetz, T Runarsson, ... Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International …, 2014 | 22 | 2014 |
| On scalable data mining techniques for earth science M Götz, M Richerzhagen, C Bodenstein, G Cavallaro, P Glock, M Riedel, ... Procedia computer science 51, 2188-2197, 2015 | 21 | 2015 |
| Deep learning approaches to building rooftop thermal bridge detection from aerial images Z Mayer, J Kahn, Y Hou, M Götz, R Volk, F Schultmann Automation in Construction 146, 104690, 2023 | 12 | 2023 |
| Learning Tree Structures from Leaves For Particle Decay Reconstruction J Kahn, I Tsaklidis, O Taubert, L Reuter, G Dujany, T Böckh, A Thaller, ... Machine Learning: Science and Technology, 2022 | 12 | 2022 |
| HeAT--a Distributed and GPU-accelerated Tensor Framework for Data Analytics M Götz, D Coquelin, C Debus, K Krajsek, C Comito, P Knechtges, ... arXiv preprint arXiv:2007.13552, 2020 | 11 | 2020 |
| Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads R Caspart, S Ziegler, A Weyrauch, H Obermaier, S Raffeiner, ... International Conference on High Performance Computing, 108-121, 2022 | 10 | 2022 |
| Scalable developments for big data analytics in remote sensing G Cavallaro, M Riedel, C Bodenstein, P Glock, M Richerzhagen, M Götz, ... 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2015 | 10 | 2015 |
| Reporting electricity consumption is essential for sustainable AI C Debus, M Piraud, A Streit, F Theis, M Götz Nature Machine Intelligence 5 (11), 1176-1178, 2023 | 8 | 2023 |
| Deep-Learning-Based 3-D Surface Reconstruction—A Survey A Farshian, M Götz, G Cavallaro, C Debus, M Nießner, JA Benediktsson, ... Proceedings of the IEEE, 2023 | 8 | 2023 |
| Process Insights into Perovskite Thin‐Film Photovoltaics from Machine Learning with In Situ Luminescence Data F Laufer, S Ziegler, F Schackmar, EA Moreno Viteri, M Götz, C Debus, ... Solar RRL 7 (7), 2201114, 2023 | 8 | 2023 |
| Machine learning-aided numerical linear algebra: Convolutional neural networks for the efficient preconditioner generation. In 2018 IEEE/ACM 9th Workshop on Latest Advances in … M Götz, H Anzt IEEE, 2018 | 8 | 2018 |
| Massively Parallel Genetic Optimization through Asynchronous Propagation of Populations O Taubert, M Weiel, D Coquelin, A Farshian, C Debus, A Schug, A Streit, ... International Conference on High Performance Computing, 106-124, 2023 | 7 | 2023 |
| Accelerating neural network training with distributed asynchronous and selective optimization (DASO) D Coquelin, C Debus, M Götz, F von der Lehr, J Kahn, M Siggel, A Streit Journal of Big Data 9 (1), 1-18, 2022 | 6 | 2022 |
| HyDe: The first open-source, Python-based, GPU-accelerated hyperspectral denoising package D Coquelin, B Rasti, M Götz, P Ghamisi, R Gloaguen, A Streit 2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution …, 2022 | 6 | 2022 |
| Evolutionary Optimization of Neural Architectures in Remote Sensing Classification Problems D Coquelin, R Sedona, M Riedel, M Götz 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 1587 …, 2021 | 6 | 2021 |
Prof. Dr.-Ing. Morris RiedelProfessor of High Performance Computing & Machine Learning, Forschungszentrum Juelich & UoIceland在 fz-juelich.de 的电子邮件经过验证
