| Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning M Lutter, C Ritter, J Peters International Conference on Learning Representations (ICLR), 2019 | 493 | 2019 |
| Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning M Lutter, C Ritter, J Peters International Conference on Learning Representations (ICLR), 2019 | 493 | 2019 |
| Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems M Lutter, K Listmann, J Peters International Conference on Intelligent Robots and Systems (IROS), 2019 | 84 | 2019 |
| Deep lagrangian networks for end-to-end learning of energy-based control for under-actuated systems M Lutter, K Listmann, J Peters International Conference on Intelligent Robots and Systems (IROS), 7718-7725, 2019 | 84 | 2019 |
| Combining physics and deep learning to learn continuous-time dynamics models M Lutter, J Peters International Journal of Robotics Research (IJRR), 2021 | 63 | 2021 |
| Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning M Lutter, J Silberbauer, J Watson, J Peters International Conference on Robotics and Automation (ICRA), 2021 | 56 | 2021 |
| Value Iteration in Continuous Actions, States and Time M Lutter, S Mannor, J Peters, D Fox, A Garg International Conference on Machone Learning (ICML), 2021 | 45 | 2021 |
| High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards K Ploeger, M Lutter, J Peters Conference on Robot Learning (CoRL), 2020 | 33 | 2020 |
| HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints M Lutter, B Belousov, K Listmann, D Clever, J Peters Conference on Robot Learning (CoRL), 2019 | 30 | 2019 |
| Learning dynamics models for model predictive agents M Lutter, L Hasenclever, A Byravan, G Dulac-Arnold, P Trochim, N Heess, ... arXiv preprint arXiv:2109.14311, 2021 | 27 | 2021 |
| Continuous-time fitted value iteration for robust policies M Lutter, B Belousov, S Mannor, D Fox, A Garg, J Peters IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 | 18 | 2022 |
| Robust Value Iteration for Continuous Control Tasks M Lutter, S Mannor, J Peters, D Fox, A Garg Robotics: Science and Systems (RSS), 2021 | 17 | 2021 |
| Online learning of an open-ended skill library for collaborative tasks D Koert, S Trick, M Ewerton, M Lutter, J Peters 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids), 1-9, 2018 | 17 | 2018 |
| A Differentiable Newton Euler Algorithm for Multi-body Model Learning M Lutter, J Silberbauer, J Watson, J Peters ICML Workshop on Inductive Biases, Invariances and Generalization in RL, 2020 | 14 | 2020 |
| A Differentiable Newton–Euler Algorithm for Real-World Robotics M Lutter Inductive Biases in Machine Learning for Robotics and Control, 9-34, 2023 | 7 | 2023 |
| Building skill learning systems for robotics M Lutter, D Clever, R Kirsten, K Listmann, J Peters 2021 IEEE 17th International Conference on Automation Science and …, 2021 | 7 | 2021 |
| Incremental learning of an open-ended collaborative skill library D Koert, S Trick, M Ewerton, M Lutter, J Peters International Journal of Humanoid Robotics 17 (01), 2050001, 2020 | 7 | 2020 |
| International Conference on Learning Representations M Lutter, C Ritter, J Peters | 7 | 2019 |
| Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning D Palenicek, M Lutter, J Carvalho, J Peters International Conference on Learning Representations (ICLR), 2023 | 5 | 2023 |
| Inductive biases in machine learning for robotics and control M Lutter Springer, 2023 | 4 | 2023 |
Jan PetersProfessor for Intelligent Autonomous Systems/TU Darmstadt, Dept. Head/German AI Research Center DFKIVerified email at ias.tu-darmstadt.de
