Efficient Off-Policy Learning for High-Dimensional Action Spaces
Fabian Otto, Philipp Becker, Vien Anh Ngo, Gerhard NeumannInternational Conference for Learning Representations (ICLR)
ICLR
International Conference for Learning Representations (ICLR)
Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning
Ge Li, Hongyi Zhou, Dominik Roth, Serges Thilges, Fabian Otto, Rudolf Lioutikov, Gerhard NeumannInternational Conference for Learning Representations (ICLR)
Differentiable Trust Region Layers for Deep Reinforcement Learning
Fabian Otto, Philipp Becker, Ngo Anh Vien, Hanna Carolin Ziesche, Gerhard NeumannInternational Conference for Learning Representations (ICLR)
CoRL
FLOWER: Democratizing Generalist Robot Policies with Efficient Vision-Language-Flow Models
Moritz Reuss, Hongyi Zhou, Marcel Rühle, Ömer Erdinç Yağmurlu, Fabian Otto, Rudolf LioutikovConference on Robot Learning (CoRL)
MP3: Movement Primitive-Based (Re-)Planning Policy
Fabian Otto, Hongyi Zhou, Onur Celik, Ge Li, Rudolf Lioutikov, Gerhard NeumannCoRL Workshop on Learning Effective Abstractions for Planning (LEAP)
Deep Black-Box Reinforcement Learning with Movement Primitives
Fabian Otto, Onur Celik, Hongyi Zhou, Hanna Ziesche, Ngo Anh Vien, Gerhard NeumannConference on Robot Learning (CoRL)
Book Chapter
Model-free Deep Reinforcement Learning – Algorithms and Applications
Fabian OttoReinforcement Learning Algorithms: Analysis and Applications. Studies in Computational Intelligence, vol 883.
RA-L
ProDMP: A Unified Perspective on Dynamic and Probabilistic Movement Primitives
Ge Li, Zeqi Jin, Michael Volpp, Fabian Otto, Rudolf Lioutikov, Gerhard NeumannIEEE Robotics and Automation Letters (RA-L)
International Conference on Intelligent Robots and Systems (IROS)
IROS
ProDMP: A Unified Perspective on Dynamic and Probabilistic Movement Primitives
Ge Li, Zeqi Jin, Michael Volpp, Fabian Otto, Rudolf Lioutikov, Gerhard NeumannIEEE Robotics and Automation Letters (RA-L)
International Conference on Intelligent Robots and Systems (IROS)
RLC
Combining Reconstruction and Contrastive Methods for Multimodal Representations in RL
Philipp Becker, Sebastian Mossburger, Fabian Otto, Gerhard NeumannReinforcement Learning Conference (RLC)
Neurips
BEAST: Efficient Tokenization of B-Splines Encoded Action Sequences for Imitation Learning
Hongyi Zhou, Weiran Liao, Xi Huang, Yucheng Tang, Fabian Otto, Xiaogang Jia, Xinkai Jiang, Simon Hilber, Ge Li, Qian Wang, Ömer Erdinç Yağmurlu, Nils Blank, Moritz Reuss, Rudolf LioutikovNeural Information Processing Systems (Neurips)
ArXiv
TROLL: Trust Regions improve Reinforcement Learning for Large Language Models
Philipp Becker, Niklas Freymuth, Serge Thilges, Fabian Otto, Gerhard NeumannArXiv