Dr Michael Kopp is a mathematical modelling specialist bringing decades of expertise in risk assessment and advanced data analysis.
He is also data scientist at Here Technologies in Zurich.
He has been instrumental in bringing about the Traffic4cast competition that builds on billions of real-world data-points to improve short-term traffic forecasting and advance our ability to capture the implicit rules underlying a complex system.
Publications
2021
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). Proceedings of the 14th International Conference on Spatial Information Theory, COSIT 2019, Regensburg, Germany, Leibniz International Proceedings in Informatics (LIPIcs), 142: 27:1–27:9. (more) (download)