
Dr Michael Kopp
Dr Michael Kopp is a mathematician bringing decades of expertise in modelling, risk assessment, advanced data analysis and machine learning.
Publications
2023
A. Gruca, F. Serva, L. Lliso, P. Rípodas, X. Calbet, P. Herruzo, J. Pihrt, R. Raevskyi, P. Šimánek, M. Choma, Y. Li, H. Dong, Y. Belousov, S. Polezhaev, B. Pulfer, M. Seo, D. Kim, S. Shin, E. Kim, S. Ahn, Y. Choi, J. Park, M. Son, S. Cho, I. Lee, C. Kim, T. Kim, S. Kang, H. Shin, D. Yoon, S. Eom, K. Shin, S.-Y. Yun, B. Le Saux, M. K. Kopp, S. Hochreiter, and D. P. Kreil (2023) Weather4cast at NeurIPS 2022: Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts. Proceedings of the NeurIPS 2022 Competitions Track, PMLR, 220, 292-313, 2023-09-04. (more) (download)
M. Neun, C. Eichenberger, Y. Xin, C. Fu, N. Wiedemann, H. Martin, M. Tomko, L. Ambühl, L. Hermes, and M. Kopp (2023) Metropolitan Segment Traffic Speeds from Massive Floating Car Data in 10 Cities. IEEE Transactions on Intelligent Transportation Systems, 2023-07-17. (more) (download)
M. Kopp (2023) The Impact of the AI Revolution on Asset Management. arXiv:2304.10212, 2023-04-20. (more) (download)
S. Chang, M. Kopp, and P. Ghamisi (2023) Dsfer-Net: A Deep Supervision and Feature Retrieval Network for Bitemporal Change Detection Using Modern Hopfield Networks. arXiv:2304.01101, 2023-04-03. (more) (download)
M. Neun, C. Eichenberger, H. Martin, M. Spanring, R. Siripurapu, D. Springer, L. Deng, C. Wu, D. Lian, M. Zhou, M. Lumiste, A. Ilie, X. Wu, C. Lyu, Q.-L. Lu, V. Mahajan, Y. Lu, J. Li, J. Li, Y.-J. Gong, F. Grötschla, J. Mathys, Y. Wei, H. Haitao, H. Fang, K. Malm, F. Tang, M. Kopp, D. Kreil, and S. Hochreiter (2023) Traffic4cast at NeurIPS 2022 – Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors. arXiv:2303.07758, 2023-03-14. (more) (download)
2022
R. Siripurapu, V. P. Patil, K. Schweighofer, M.-C. Dinu, T. Schmied, L. E. F. Diez, M. Holzleitner, H. Eghbal-Zadeh, M. K. Kopp, and S. Hochreiter (2022) InfODist: Online Distillation with Informative Rewards Improves Generalization in Curriculum Learning. Deep Reinforcement Learning Workshop at NeurIPS 2022, 2022-12-09. (more) (download)
A. Fürst, E. Rumetshofer, J. Lehner, V. T. Tran, F. Tang, H. Ramsauer, D. Kreil, M. Kopp, G. Klambauer, A. Bitto, and S. Hochreiter (2022) CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP. Advances in Neural Information Processing Systems (NeurIPS 2022), 35, 20450-20468, 2022-12-06. (more) (download)
I. Svogor, C. Eichenberger, M. Spanring, M. Neun, and M. Kopp (2022) Profiling and Improving the PyTorch Dataloader for High-Latency Storage: A Technical Report. arXiv:2211.04908, 2022-11-09. (more) (download)
S. Chang, M. Kopp, and P. Ghamisi (2022) Sketched Multi-view Subspace Learning for Hyperspectral Anomalous Change Detection. IEEE Transactions on Geoscience and Remote Sensing, 60, 2022-11-09. (more) (download)
O. Ghorbanzadeh, Y. Xu, P. Ghamisi, M. Kopp, and D. Kreil (2022) Landslide4Sense: Reference Benchmark Data and Deep Learning Models for Landslide Detection. IEEE Transactions on Geoscience and Remote Sensing, 60, 2022-10-17. (more) (download)
M. Krenn, L. Buffoni, B. Coutinho, S. Eppel, J. G. Foster, A. Gritsevskiy, H. Lee, Y. Lu, J. P. Moutinho, N. Sanjabi, R. Sonthalia, N. M. Tran, F. Valente, Y. Xie, R. Yu, and M. Kopp (2022) Predicting the Future of AI with AI: High-Quality Link Prediction in an Exponentially Growing Knowledge Network. arXiv:2210.00881, 2022-09-23. (more) (download)
Y. Xu, W. Yu, P. Ghamisi, M. Kopp, and S. Hochreiter (2022) Txt2Img-MHN: Remote Sensing Image Generation from Text Using Modern Hopfield Networks. arXiv:2208.04441, 2022-08-08. (more) (download)
S. Chang, M. Kopp, and P. Ghamisi (2022) A Deep Feature Retrieved Network for Bitemporal Remote Sensing Image Change Detection. CEUR Workshop Proceedings, 3207, 2022-07-25. (more) (download)
P. Ghamisi, O. Ghorbanzadeh, Y. Xu, P. Herruzo, D. Kreil, M. Kopp, and S. Hochreiter (2022) The Landslide4Sense Competition 2022. CEUR Workshop Proceedings, 3207, 2022-07-25. (more) (download)
C. Eichenberger, M. Neun, H. Martin, P. Herruzo, M. Spanring, Y. Lu, S. Choi, V. Konyakhin, N. Lukashina, A. Shpilman, N. Wiedemann, M. Raubal, B. Wang, H. L. Vu, R. Mohajerpoor, C. Cai, I. Kim, L. Hermes, A. Melnik, R. Velioglu, M. Vieth, M. Schilling, A. Bojesomo, H. Al Marzouqi, P. Liatsis, J. Santokhi, D. Hillier, Y. Yang, J. Sarwar, A. Jordan, E. Hewage, D. Jonietz, F. Tang, A. Gruca, M. Kopp, D. Kreil, and S. Hochreiter (2022) Traffic4cast at NeurIPS 2021 – Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes. NeurIPS 2021 Competitions and Demonstrations Track, PMLR, 176, 97-112, 2022-07-20. (more) (download)
2021
P. Herruzo, A. Gruca, L. Lliso, X. Calbet, P. Rípodas, S. Hochreiter, M. Kopp, and D. P. Kreil (2021) High-Resolution Multi-Channel Weather Forecasting – First Insights on Transfer Learning from the Weather4cast Competitions 2021. 2021 IEEE International Conference on Big Data, 5750-5757, 2021-12-15. (more) (download)
A. Gruca, P. Herruzo, P. Rípodas, A. Kucik, C. Briese, M. K. Kopp, S. Hochreiter, P. Ghamisi, and D. P. Kreil (2021) CDCEO’21 – First Workshop on Complex Data Challenges in Earth Observation. Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 4878–4879, 2021-10-26. (more) (download)
M. Kopp, D. Kreil, M. Neun, D. Jonietz, H. Martin, P. Herruzo, A. Gruca, A. Soleymani, F. Wu, Y. Liu, J. Xu, J. Zhang, J. Santokhi, A. Bojesomo, H. Al Marzouqi, P. Liatsis, P. H. Kwok, Q. Qi, and S. Hochreiter (2021) Traffic4cast at NeurIPS 2020 – Yet More on the Unreasonable Effectiveness of Gridded Geo-Spatial Processes. Proceedings of the NeurIPS 2020 Competition and Demonstration Track, PMLR, 133, 325-343, 2021. (more) (download)
F. Tang & M. Kopp (2021) A Remark on a Paper of Krotov and Hopfield. arXiv:2105.15034, 2021-06-03. (more) (download)
2020
T. Adler, J. Brandstetter, M. Widrich, A. Mayr, D. Kreil, M. Kopp, G. Klambauer, and S. Hochreiter (2020) Cross-Domain Few-Shot Learning by Representation Fusion. arXiv:2010.06498, 2020-10-13. (more) (download)
D. P. Kreil, M. K. Kopp, D. Jonietz, M. Neun, A. Gruca, P. Herruzo, H. Martin, A. Soleymani, and S. Hochreiter (2020) The surprising efficiency of framing geo-spatial time series forecasting as a video prediction task – Insights from the IARAI Traffic4cast Competition at NeurIPS 2019. Proceedings of the NeurIPS 2019 Competition and Demonstration Track, PMLR, 123, 232-241, 2020-08-19. (more) (download)
H. Ramsauer, B. Schäfl, J. Lehner, P. Seidl, M. Widrich, L. Gruber, M. Holzleitner, M. Pavlović, G. K. Sandve, V. Greiff, D. Kreil, M. Kopp, G. Klambauer, J. Brandstetter, and S. Hochreiter (2020) Hopfield Networks is All You Need. arXiv:2008.02217, 2020-08-06. (more) (download)
2019
D. Jonietz & M. Kopp (2019) Towards Modeling Geographical Processes with Generative Adversarial Networks (GANs). 14th International Conference on Spatial Information Theory (COSIT 2019), Leibniz International Proceedings in Informatics (LIPIcs), 142, 27, 2019-09-03. (more) (download)