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4 Publications
2024 | Preprint | LibreCat-ID: 55159 | 
Offen, C. (n.d.). Machine learning of discrete field theories with guaranteed convergence and uncertainty quantification.
LibreCat
| Files available
| arXiv
2023 | Conference Paper | LibreCat-ID: 42163 |
Offen, C., & Ober-Blöbaum, S. (2023). Learning discrete Lagrangians for variational PDEs from data and detection of travelling waves. In F. Nielsen & F. Barbaresco (Eds.), Geometric Science of Information (Vol. 14071, pp. 569–579). Springer, Cham. https://doi.org/10.1007/978-3-031-38271-0_57
LibreCat
| Files available
| DOI
| arXiv
2022 | Conference Paper | LibreCat-ID: 26539 |
Götte, R.-S., & Timmermann, J. (2022). Composed Physics- and Data-driven System Identification for Non-autonomous Systems in Control Engineering. 2022 3rd International Conference on Artificial Intelligence, Robotics and Control (AIRC), 67–76. https://doi.org/10.1109/AIRC56195.2022.9836982
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| DOI
| Download (ext.)
2022 | Conference Paper | LibreCat-ID: 31066
Schön, O., Götte, R.-S., & Timmermann, J. (2022). Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems. 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), 55(12), 19–24. https://doi.org/10.1016/j.ifacol.2022.07.282
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