| Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning M Lutter, C Ritter, J Peters International Conference on Learning Representations (ICLR), 2019 | 343 | 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 | 55* | 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 | 47 | 2019 |
| 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 | 32 | 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 | 25 | 2021 |
| 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 | 22 | 2019 |
| High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards K Ploeger, M Lutter, J Peters Conference on Robot Learning (CoRL), 2020 | 20 | 2020 |
| 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 | 19 | 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 | 15 | 2018 |
| Robust Value Iteration for Continuous Control Tasks M Lutter, S Mannor, J Peters, D Fox, A Garg Robotics: Science and Systems (RSS), 2021 | 14 | 2021 |
| 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 | 11 | 2020 |
| Combining physics and deep learning to learn continuous-time dynamics models M Lutter, J Peters International Journal of Robotics Research (IJRR), 2021 | 9 | 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 | 6 | 2020 |
| 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 | 5 | 2021 |
| International Conference on Learning Representations M Lutter, C Ritter, J Peters | 5 | 2019 |
| A Differentiable Newton–Euler Algorithm for Real-World Robotics M Lutter Inductive Biases in Machine Learning for Robotics and Control, 9-34, 2023 | 3 | 2023 |
| Continuous-time fitted value iteration for robust policies M Lutter Inductive Biases in Machine Learning for Robotics and Control, 71-111, 2023 | 3 | 2023 |
| Revisiting Model-based Value Expansion D Palenicek, M Lutter, J Peters arXiv preprint arXiv:2203.14660, 2022 | 1 | 2022 |
| Trajectory optimization of energy consumption and expected service life of a robotic system F Stuhlenmiller, D Clever, S Rinderknecht, M Lutter, J Peters 2021 IEEE/ASME International Conference on Advanced Intelligent Mechatronics …, 2021 | 1 | 2021 |
| Differential Equations as a Model Prior for Deep Learning and its Applications in Robotics M Lutter, J Peters ICLR 2020 Workshop on Integration of Deep Neural Models and Differential …, 2020 | 1 | 2020 |
Jan PetersProfessor for Intelligent Autonomous Systems at Technische Universität DarmstadtBestätigte E-Mail-Adresse bei ias.tu-darmstadt.de
