C. Robinson, K. Malkin, N. Jojic, H. Chen, R. Qin, C. Xiao, M. Schmitt, P. Ghamisi, R. Hansch, and N. Yokoya (2021) Global Land Cover Mapping with Weak Supervision: Outcome of the 2020 IEEE GRSS Data Fusion Contest.  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021-04-03. (more) (download)

J. Yue, L. Fang, H. Rahmani, and P. Ghamisi (2021) Self-Supervised Learning With Adaptive Distillation for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing, 1-13, 2021-02-22. (more) (download)

P.-J. Hoedt, F. Kratzert, D. Klotz, C. Halmich, M. Holzleitner, G. Nearing, S. Hochreiter, and G. Klambauer (2021) MC-LSTM: Mass-Conserving LSTM. arXiv:2101.05186, 2021-01-13. (more) (download)


D. Klotz, F. Kratzert, M. Gauch, A. K. Sampson, G. Klambauer, S. Hochreiter, and G. Nearing (2020) Uncertainty Estimation with Deep Learning for Rainfall-Runoff Modelling. EarthArXiv, 2020-12-17. (more) (download)

M. Gauch, D. Klotz, F. Kratzert, G. Nearing, S. Hochreiter, and a. J. Lin (2020) A Machine Learner’s Guide to Streamflow Prediction. NeurIPS Workshop: AI for Earth Sciences, 2020-12-12. (more) (download)

M. Holzleitner, L. Gruber, J. Arjona-Medina, J. Brandstetter, and S. Hochreiter (2020) Convergence Proof for Actor-Critic Methods Applied to PPO and RUDDER. arXiv:2012.01399, 2020-12-02. (more) (download)

L. Servadei, J. Zheng, J. Arjona-Medina, M. Werner, V. Esen, S. Hochreiter, W. Ecker, and R. Wille (2020) Cost Optimization at Early Stages of Design Using Deep Reinforcement Learning. Proceedings of the 2020 ACM/IEEE Workshop on Machine Learning for CAD, 37-42, 2020-11-16. (more) (download)

S. Kimeswenger, P. Tschandl, P. Noack, M. Hofmarcher, E. Rumetshofer, H. Kindermann, R. Silye, S. Hochreiter, M. Kaltenbrunner, E. Guenova, G. Klambauer, and W. Hoetzenecker (2020) Artificial neural networks and pathologists recognize basal cell carcinomas based on different histological patterns. Modern Pathology, 1-9, 2020-11-13. (more) (download)

P. Renz, D. Van Rompaey, J. K. Wegner, S. Hochreiter, and G. Klambauer (2020) On failure modes in molecule generation and optimization. Drug Discovery Today: Technologies, 32, 55-63, 2020-10-24. (more) (download)

M. Gauch, F. Kratzert, D. Klotz, G. Nearing, J. Lin, and S. Hochreiter (2020) Rainfall-Runoff Prediction at Multiple Timescales with a Single Long Short-Term Memory Network. arXiv:2010.07921, 2020-10-15. (more) (download)

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)

V. P. Patil, M. Hofmarcher, M.-C. Dinu, M. Dorfer, P. M. Blies, J. Brandstetter, J. A. Arjona-Medina, and S. Hochreiter (2020) Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution. arXiv:2009.14108, 2020-09-29. (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)

P. Herruzo & J. L. Larriba-Pey (2020) Recurrent Autoencoder with Skip Connections and Exogenous Variables for Traffic Forecasting. Proceedings of the NeurIPS 2019 Competition and Demonstration Track, PMLR 123:47-55, 2020-08-19. (more) (download)

H. Martin, D. Bucher, Y. Hong, R. Buffat, C. Rupprecht, and M. Raubal (2020) Graph-ResNets for short-term traffic forecasts in almost unknown cities. Proceedings of the NeurIPS 2019 Competition and Demonstration Track, PMLR 123:153-163, 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)

M. Widrich, B. Schäfl, H. Ramsauer, M. Pavlović, L. Gruber, M. Holzleitner, J. Brandstetter, G. K. Sandve, V. Greiff, S. Hochreiter, and G. Klambauer (2020) Modern Hopfield Networks and Attention for Immune Repertoire Classification. arXiv:2007.13505, 2020-07-16. (more) (download)

M. M. Cutchan, S. Özdal‐Oktay, and I. Giannopoulos (2020) Semantic‐based urban growth prediction. Transactions in GIS. 00: 1– 22. 2020-07-14. (more) (download)

A. Mitterecker, A. Hofmann, K. M. Trentino, A. Lloyd, M. F. Leahy, K. Schwarzbauer, T. Tschoellitsch, C. Böck, S. Hochreiter, and J. Meier (2020) Machine learning–based prediction of transfusion. Transfusion, 60, 1977–1986, 2020-06-28. (more) (download)

F. Kratzert, D. Klotz, S. Hochreiter, and G. Nearing (2020) A note on leveraging synergy in multiple meteorological datasets with deep learning for rainfall-runoff modeling. EarthArXiv, 2020-05-06. (more) (download)

N. Sturm, A. Mayr, T. L. Van, V. Chupakhin, H. Ceulemans, J. Wegner, J.-F. Golib-Dzib, N. Jeliazkova, Y. Vandriessche, S. Böhm, V. Cima, J. Martinovic, N. Greene, T. V. Aa, T. J. Ashby, S. Hochreiter, O. Engkvist, G. Klambauer, and H. Chen (2020) Industry-scale application and evaluation of deep learning for drug target prediction. Journal of Cheminformatics, 12, 1-13, 2020-04-19. (more) (download)

M. Hofmarcher, A. Mayr, E. Rumetshofer, P. Ruch, P. Renz, J. Schimunek, P. Seidl, A. Vall, M. Widrich, S. Hochreiter, and G. Klambauer (2020) Large-Scale Ligand-Based Virtual Screening for SARS-CoV-2 Inhibitors Using Deep Neural Networks. SSRN 3561442, 2020-03-23. (more) (download)

A. Mayr, G. Klambauer, T. Unterthiner, and S. Hochreiter (2020) The LSC Benchmark Dataset: Technical Appendix and Partial Reanalysis. 2020-02-12. (more) (download)


F. Kratzert, D. Klotz, M. Herrnegger, A. K. Sampson, S. Hochreiter, and G. S. Nearing (2019) Toward Improved Predictions in Ungauged Basins: Exploiting the Power of Machine Learning. Water Resources Research. 55, 12, 11344-11354. 2019-12-23. (more) (download)


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