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2020 – today
- 2023
[b2]Michael Lutter:
Inductive Biases in Machine Learning for Robotics and Control. Springer Tracts in Advanced Robotics 156, Springer 2023, ISBN 978-3-031-37831-7, pp. 1-119- [j3]Michael Lutter
, Jan Peters:
Combining physics and deep learning to learn continuous-time dynamics models. Int. J. Robotics Res. 42(3): 83-107 (2023) - [j2]Michael Lutter, Boris Belousov, Shie Mannor, Dieter Fox, Animesh Garg, Jan Peters:
Continuous-Time Fitted Value Iteration for Robust Policies. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5534-5548 (2023) - [c11]Daniel Palenicek, Michael Lutter, Joao Carvalho, Jan Peters:
Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning. ICLR 2023 - [i14]Daniel Palenicek, Michael Lutter, Joao Carvalho, Jan Peters:
Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning. CoRR abs/2303.03955 (2023) - 2022
- [i13]Daniel Palenicek, Michael Lutter, Jan Peters:
Revisiting Model-based Value Expansion. CoRR abs/2203.14660 (2022) - 2021
- [b1]Michael Lutter:
Inductive Biases in Machine Learning for Robotics and Control. TU Darmstadt, Germany, 2021 - [c10]Florian Stuhlenmiller, Debora Clever, Stephan Rinderknecht, Michael Lutter, Jan Peters:
Trajectory Optimization of Energy Consumption and Expected Service Life of a Robotic System. AIM 2021: 842-847 - [c9]Michael Lutter, Debora Clever, René Kirsten, Kim Listmann, Jan Peters:
Building Skill Learning Systems for Robotics. CASE 2021: 1878-1883 - [c8]Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg:
Value Iteration in Continuous Actions, States and Time. ICML 2021: 7224-7234 - [c7]Michael Lutter, Johannes Silberbauer, Joe Watson, Jan Peters:
Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning. ICRA 2021: 4163-4170 - [c6]Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg:
Robust Value Iteration for Continuous Control Tasks. Robotics: Science and Systems 2021 - [i12]Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg:
Value Iteration in Continuous Actions, States and Time. CoRR abs/2105.04682 (2021) - [i11]Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg:
Robust Value Iteration for Continuous Control Tasks. CoRR abs/2105.12189 (2021) - [i10]Michael Lutter, Leonard Hasenclever, Arunkumar Byravan, Gabriel Dulac-Arnold, Piotr Trochim, Nicolas Heess, Josh Merel, Yuval Tassa:
Learning Dynamics Models for Model Predictive Agents. CoRR abs/2109.14311 (2021) - [i9]Michael Lutter, Jan Peters:
Combining Physics and Deep Learning to learn Continuous-Time Dynamics Models. CoRR abs/2110.01894 (2021) - [i8]Michael Lutter, Boris Belousov, Shie Mannor, Dieter Fox, Animesh Garg, Jan Peters:
Continuous-Time Fitted Value Iteration for Robust Policies. CoRR abs/2110.01954 (2021) - [i7]Michael Lutter, Johannes Silberbauer, Joe Watson, Jan Peters:
A Differentiable Newton-Euler Algorithm for Real-World Robotics. CoRR abs/2110.12422 (2021) - 2020
- [j1]Dorothea Koert, Susanne Trick, Marco Ewerton, Michael Lutter, Jan Peters:
Incremental Learning of an Open-Ended Collaborative Skill Library. Int. J. Humanoid Robotics 17(1): 2050001:1-2050001:23 (2020) - [c5]Kai Ploeger, Michael Lutter, Jan Peters:
High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards. CoRL 2020: 642-653 - [i6]Michael Lutter, Johannes Silberbauer, Joe Watson, Jan Peters:
A Differentiable Newton Euler Algorithm for Multi-body Model Learning. CoRR abs/2010.09802 (2020) - [i5]Kai Ploeger, Michael Lutter, Jan Peters:
High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards. CoRR abs/2010.13483 (2020) - [i4]Michael Lutter, Johannes Silberbauer, Joe Watson, Jan Peters:
Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning. CoRR abs/2011.01734 (2020)
2010 – 2019
- 2019
- [c4]Michael Lutter, Boris Belousov, Kim Listmann, Debora Clever, Jan Peters:
HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints. CoRL 2019: 640-650 - [c3]Michael Lutter, Christian Ritter, Jan Peters:
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning. ICLR (Poster) 2019 - [c2]Michael Lutter, Kim Listmann, Jan Peters:
Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems. IROS 2019: 7718-7725 - [i3]Michael Lutter, Kim Listmann, Jan Peters:
Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems. CoRR abs/1907.04489 (2019) - [i2]Michael Lutter, Christian Ritter, Jan Peters:
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning. CoRR abs/1907.04490 (2019) - [i1]Michael Lutter, Boris Belousov, Kim Listmann, Debora Clever, Jan Peters:
HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints. CoRR abs/1909.06153 (2019) - 2018
- [c1]Dorothea Koert, Susanne Trick, Marco Ewerton, Michael Lutter, Jan Peters:
Online Learning of an Open-Ended Skill Library for Collaborative Tasks. Humanoids 2018: 1-9
Coauthor Index
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