Deep Learning

P. Ghamisi, K. R. Shahi, P. Duan, B. Rasti, S. Lorenz, R. Booysen, S. Thiele, I. C. C. Acosta, M. Kirsch, and R. Gloaguen (2021) The Potential of Machine Learning for a More Responsible Sourcing of Critical Raw Materials. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021-09-01. (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. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM ’21), November 1–5, 2021, Virtual Event, QLD, Australia. ACM, New York, NY, USA. (in press). (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)

M. Mc Cutchan, A. J. Comber, I. Giannopoulos, and a. M. Canestrini (2021) Semantic Boosting: Enhancing Deep Learning Based LULC Classification. Remote Sensing, 13, 16, 3197, 2021-08-12. (more) (download)

J. Yue, D. Zhu, L. Fang, P. Ghamisi, and Y. Wang (2021) Adaptive Spatial Pyramid Constraint for Hyperspectral Image Classification with Limited Training Samples. IEEE Transactions on Geoscience and Remote Sensing, 2021-07-20. (more) (download)

O. Ghorbanzadeh, A. Crivellari, P. Ghamisi, H. Shahabi, and T. Blaschke (2021) A Comprehensive Transferability Evaluation of U-Net and ResU-Net for Landslide Detection from Sentinel-2 Data. Scientific Reports, 11, 14629, 2021-07-16. (more) (download)

B. Rasti, Y. Chang, E. Dalsasso, L. Denis, and P. Ghamisi (2021) Image Restoration for Remote Sensing: Overview and Toolbox. arXiv:2107.00557, 2021-07-01. (more) (download)

A. Mayr, S. Lehner, A. Mayrhofer, C. Kloss, S. Hochreiter, and J. Brandstetter (2021) Boundary Graph Neural Networks for 3D Simulations. arXiv:2106.11299, 2021-06-21. (more) (download)

F. Kratzert, D. Klotz, S. Hochreiter, and G. Nearing (2021) A Note on Leveraging Synergy in Multiple Meteorological Datasets with Deep Learning for Rainfall-Runoff Modeling. Hydrology and Earth System Sciences, 25, 5, 2685-2703, 2021-05-20. (more) (download)

F. Kratzert, M. Gauch, G. Nearing, S. Hochreiter, and D. Klotz (2021) Rainfall-Runoff Modeling with Long Short-Term Memory Networks (LSTM)—an Overview. Österreichische Wasser-und Abfallwirtschaft, 2021-05-17. (more) (download)

A. Mayr, S. Lehner, A. Mayrhofer, C. Kloss, S. Hochreiter, and J. Brandstetter (2021) Learning 3D Granular Flow Simulations. arXiv: 2105.01636, 2021-05-04. (more) (download)

A. Vall, Y. Sabnis, J. Shi, R. Class, S. Hochreiter, and G. Klambauer (2021) The Promise of AI for DILI Prediction. Frontiers in Artificial Intelligence, 4, 638410, 2021-04-14. (more) (download)

B. Rasti, B. Koirala, P. Scheunders, and P. Ghamisi (2021) UnDIP: Hyperspectral Unmixing Using Deep Image Prior. IEEE Transactions on Geoscience and Remote Sensing, 2021-03-31. (more) (download)

P. M. Winter, S. Eder, J. Weissenböck, C. Schwald, T. Doms, T. Vogt, S. Hochreiter, and B. Nessler (2021) Trusted Artificial Intelligence: Towards Certification of Machine Learning Applications. arXiv:2103.16910, 2021-03-31. (more) (download)

D. Klotz, F. Kratzert, M. Gauch, A. K. Sampson, G. Klambauer, S. Hochreiter, and G. Nearing (2021) Uncertainty Estimation with Deep Learning for Rainfall-Runoff Modelling. Hydrology and Earth System Sciences, under review, 2021-03-15. (more) (download)

M. Pavlovic, L. Scheffer, K. Motwani, C. Kanduri, R. Kompova, N. Vazov, K. Waagan, F. LM Bernal, A. A. Costa, B. Corrie, R. Akbar, G. S. Al Hajj, G. Balaban, T. M. Brusko, M. Chernigovskaya, S. Christley, L. G. Cowell, R. Frank, I. Grytten, S. Gundersen, I. H. Haff, S. Hochreiter, E. Hovig, P.-H. Hsieh, G. Klambauer, M. L. Kuijjer, C. Lund-Andersen, A. Martini, T. Minotto, J. Pensar, K. Rand, E. Riccardi, P. A. Robert, A. Rocha, A. Slabodkin, I. Snapkov, L. M. Sollid, D. Titov, C. R. Weber, M. Widrich, G. Yaari, V. Greiff, and G. K. Sandve (2021) immuneML: an Ecosystem for Machine Learning Analysis of Adaptive Immune Receptor Repertoires. bioRxiv, 2021-03-15. (more) (download)

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, 2021-03-04. (more) (download)

F. Kratzert, D. Klotz, M. Gauch, C. Klingler, G. Nearing, and S. Hochreiter (2021) Large-Scale River Network Modeling Using Graph Neural Networks. EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13375, 2021-03-03. (more) (download)

D. Klotz, F. Kratzert, M. Gauch, A. K. Sampson, G. Klambauer, J. Brandstetter, S. Hochreiter, and G. Nearing (2021) Uncertainty Estimation with LSTM Based Rainfall-Runoff Models. EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13308, 2021-03-03. (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)

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, 34, 5, 895–903, 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)

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)