Michael Kopp
Zitiert von
Zitiert von
Hopfield networks is all you need
H Ramsauer, B Schäfl, J Lehner, P Seidl, M Widrich, T Adler, L Gruber, ...
arXiv preprint arXiv:2008.02217, 2020
Asynchronous federated learning for geospatial applications
MR Sprague, A Jalalirad, M Scavuzzo, C Capota, M Neun, L Do, M Kopp
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2018
Cloob: Modern hopfield networks with infoloob outperform clip
A Fürst, E Rumetshofer, J Lehner, VT Tran, F Tang, H Ramsauer, D Kreil, ...
Advances in neural information processing systems 35, 20450-20468, 2022
Landslide4sense: Reference benchmark data and deep learning models for landslide detection
O Ghorbanzadeh, Y Xu, P Ghamisi, M Kopp, D Kreil
arXiv preprint arXiv:2206.00515, 2022
Asynchronous parameter aggregation for machine learning
M Kopp, M Neun, M Sprague, A Jalalirad, M Scavuzzo, C Capota
US Patent US20190311298A1, 2022
Cross-domain few-shot learning by representation fusion
T Adler, J Brandstetter, M Widrich, A Mayr, D Kreil, MK Kopp, ...
The surprising efficiency of framing geo-spatial time series forecasting as a video prediction task–insights from the iarai traffic4cast competition at neurips 2019
DP Kreil, MK Kopp, D Jonietz, M Neun, A Gruca, P Herruzo, H Martin, ...
NeurIPS 2019 Competition and Demonstration Track, 232-241, 2020
Media unit retrieval and related processes
M Elkaim, M Kopp, K Korjus
US Patent 10,769,197, 2020
Traffic4cast at neurips 2020- yet more on the unreasonable effectiveness of gridded geo-spatial processes
M Kopp, D Kreil, M Neun, D Jonietz, H Martin, P Herruzo, A Gruca, ...
NeurIPS 2020 Competition and Demonstration Track, 325-343, 2021
High-resolution multi-channel weather forecasting–First insights on transfer learning from the Weather4cast Competitions 2021
P Herruzo, A Gruca, L Lliso, X Calbet, P Rípodas, S Hochreiter, M Kopp, ...
2021 IEEE International Conference on Big Data (Big Data), 5750-5757, 2021
Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network
M Krenn, L Buffoni, B Coutinho, S Eppel, JG Foster, A Gritsevskiy, H Lee, ...
Nature Machine Intelligence 5 (11), 1326-1335, 2023
Txt2Img-MHN: Remote sensing image generation from text using modern Hopfield networks
Y Xu, W Yu, P Ghamisi, M Kopp, S Hochreiter
IEEE Transactions on Image Processing, 2023
CDCEO'21-First Workshop on Complex Data Challenges in Earth Observation
A Gruca, P Herruzo, P Rípodas, A Kucik, C Briese, MK Kopp, S Hochreiter, ...
Proceedings of the 30th ACM International Conference on Information …, 2021
Traffic4cast at NeurIPS 2021-Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes
C Eichenberger, M Neun, H Martin, P Herruzo, M Spanring, Y Lu, S Choi, ...
NeurIPS 2021 Competitions and Demonstrations Track, 97-112, 2022
Sketched Multiview Subspace Learning for Hyperspectral Anomalous Change Detection
S Chang, M Kopp, P Ghamisi
IEEE Transactions on Geoscience and Remote Sensing 60, 1-12, 2022
A remark on a paper of Krotov and Hopfield [arXiv: 2008.06996]
F Tang, M Kopp
arXiv preprint arXiv:2105.15034, 2021
Weather4cast at neurips 2022: Super-resolution rain movie prediction under spatio-temporal shifts
A Gruca, F Serva, L Lliso, P Rípodas, X Calbet, P Herruzo, J Pihrt, ...
NeurIPS 2022 Competition Track, 292-313, 2023
Fréchet algebras of finite type
MK Kopp
Archiv der Mathematik 83, 217-228, 2004
Dsfer-Net: A Deep Supervision and Feature Retrieval Network for Bitemporal Change Detection Using Modern Hopfield Networks
S Chang, M Kopp, P Ghamisi
arXiv preprint arXiv:2304.01101, 2023
Traffic4cast at NeurIPS 2022–Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors
M Neun, C Eichenberger, H Martin, M Spanring, R Siripurapu, D Springer, ...
NeurIPS 2022 Competition Track, 251-278, 2022
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