Andreas Schlaginhaufen
EPFL STI IGM SYCAMORE
ME C1 402 (Bâtiment ME)
Station 9
1015 Lausanne
Web site: Web site: https://www.epfl.ch/labs/sycamore/
Biography
Andreas Schlaginhaufen received his Bachelor and Master Degree in Electrical Engineering and Information Technology from ETH Zurich, Switzerland. Furthermore, he studied for an exchange semester at the University of Toronto, Canada. He interned in the power grid development team of EWZ Zurich, as well as in the learning & adaptive systems group at ETH Zurich. In his master thesis he investigated stable deep dynamics models for partially observed or time-delayed dynamical systems. His current research interests are centered around safety aspects in reinforcement learning, learning from human demonstrations, and learning in multiagent systems.Publications
Selected publications
| Andreas Schlaginhaufen, Maryam Kamgarpour Proceedings of the 40th International Conference on Machine Learning |
Identifiability and Generalizability in Constrained Inverse Reinforcement Learning |
| Andreas Schlaginhaufen, Philippe Wenk, Andreas Krause, Florian Dörfler Advances in Neural Information Processing Systems 34 (NeurIPS 2021) |
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems |