Inverse Optimal Control Adapted to the Noise Characteristics of the Human Sensorimotor System M Schultheis, D Straub, CA Rothkopf Advances in Neural Information Processing Systems (NeurIPS) 34, 9429-9442, 2021 | 29 | 2021 |
Receding Horizon Curiosity M Schultheis, B Belousov, H Abdulsamad, J Peters Conference on Robot Learning (CoRL), 1278-1288, 2020 | 25 | 2020 |
Reinforcement Learning with Non-Exponential Discounting M Schultheis, CA Rothkopf, H Koeppl Advances in Neural Information Processing Systems (NeurIPS) 35, 3649-3662, 2022 | 16 | 2022 |
POMDPs in Continuous Time and Discrete Spaces B Alt, M Schultheis, H Koeppl Advances in Neural Information Processing Systems (NeurIPS) 33, 13151-13162, 2020 | 15 | 2020 |
Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs D Straub, M Schultheis, H Koeppl, CA Rothkopf Advances in Neural Information Processing Systems 36, 2024 | 3* | 2024 |
Belief Space Model Predictive Control for Approximately Optimal System Identification B Belousov, H Abdulsamad, M Schultheis, J Peters 4th Multidisciplinary Conference on Reinforcement Learning and Decision …, 2019 | 3 | 2019 |
Probabilistic Trajectory Segmentation by Means of Hierarchical Dirichlet Process Switching Linear Dynamical Systems M Sieb, M Schultheis, S Szelag, R Lioutikov, J Peters arXiv preprint arXiv:1806.06063, 2018 | | 2018 |