
Dr David Kreil
Dr Kreil is a leading data scientist with expertise in modelling high dimensional spaces, recently collaborating with the US FDA on benchmarking and calibrating next generation sequencing assays. He has chaired international data analysis contests in the scientific community at CAMDA since 2008.
He has since brought his expertise to establish the Traffic4cast contest as a Competition Track at NeurIPS 2019. His current research interests include paradigm change detection, robustness, sensor fusion, and informative priors.
He is also a professor at Boku University Vienna.
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, 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
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)
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)
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)
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)