Publications by Topic

• Model-free 5
• Trust Regions 5
• Movement Primitives 4
• Vision-Language-Action Models 2
• Imitation Learning 2
• Review 1
• Representation Learning 1
• Large Language Models 1
• Model-free Reinforcement Learning 1

Model-free

Efficient Off-Policy Learning for High-Dimensional Action Spaces

Fabian Otto, Philipp Becker, Vien Anh Ngo, Gerhard Neumann
International Conference for Learning Representations (ICLR)

MP3: Movement Primitive-Based (Re-)Planning Policy

Fabian Otto, Hongyi Zhou, Onur Celik, Ge Li, Rudolf Lioutikov, Gerhard Neumann
CoRL 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 Neumann
Conference on Robot Learning (CoRL)

Differentiable Trust Region Layers for Deep Reinforcement Learning

Fabian Otto, Philipp Becker, Ngo Anh Vien, Hanna Carolin Ziesche, Gerhard Neumann
International Conference for Learning Representations (ICLR)

Model-free Deep Reinforcement Learning – Algorithms and Applications

Fabian Otto
Reinforcement Learning Algorithms: Analysis and Applications. Studies in Computational Intelligence, vol 883.

Trust Regions

Efficient Off-Policy Learning for High-Dimensional Action Spaces

Fabian Otto, Philipp Becker, Vien Anh Ngo, Gerhard Neumann
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 Neumann
International Conference for Learning Representations (ICLR)

MP3: Movement Primitive-Based (Re-)Planning Policy

Fabian Otto, Hongyi Zhou, Onur Celik, Ge Li, Rudolf Lioutikov, Gerhard Neumann
CoRL 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 Neumann
Conference on Robot Learning (CoRL)

Differentiable Trust Region Layers for Deep Reinforcement Learning

Fabian Otto, Philipp Becker, Ngo Anh Vien, Hanna Carolin Ziesche, Gerhard Neumann
International Conference for Learning Representations (ICLR)

Movement Primitives

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 Neumann
International Conference for Learning Representations (ICLR)

MP3: Movement Primitive-Based (Re-)Planning Policy

Fabian Otto, Hongyi Zhou, Onur Celik, Ge Li, Rudolf Lioutikov, Gerhard Neumann
CoRL Workshop on Learning Effective Abstractions for Planning (LEAP)

ProDMP: A Unified Perspective on Dynamic and Probabilistic Movement Primitives

Ge Li, Zeqi Jin, Michael Volpp, Fabian Otto, Rudolf Lioutikov, Gerhard Neumann
IEEE Robotics and Automation Letters (RA-L)
International Conference on Intelligent Robots and Systems (IROS)

Deep Black-Box Reinforcement Learning with Movement Primitives

Fabian Otto, Onur Celik, Hongyi Zhou, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann
Conference on Robot Learning (CoRL)

Vision-Language-Action Models

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 Lioutikov
Neural Information Processing Systems (Neurips)

FLOWER: Democratizing Generalist Robot Policies with Efficient Vision-Language-Flow Models

Moritz Reuss, Hongyi Zhou, Marcel Rühle, Ömer Erdinç Yağmurlu, Fabian Otto, Rudolf Lioutikov
Conference on Robot Learning (CoRL)

Imitation Learning

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 Lioutikov
Neural Information Processing Systems (Neurips)

FLOWER: Democratizing Generalist Robot Policies with Efficient Vision-Language-Flow Models

Moritz Reuss, Hongyi Zhou, Marcel Rühle, Ömer Erdinç Yağmurlu, Fabian Otto, Rudolf Lioutikov
Conference on Robot Learning (CoRL)

Review

Model-free Deep Reinforcement Learning – Algorithms and Applications

Fabian Otto
Reinforcement Learning Algorithms: Analysis and Applications. Studies in Computational Intelligence, vol 883.

Representation Learning

Combining Reconstruction and Contrastive Methods for Multimodal Representations in RL

Philipp Becker, Sebastian Mossburger, Fabian Otto, Gerhard Neumann
Reinforcement Learning Conference (RLC)

Large Language Models

TROLL: Trust Regions improve Reinforcement Learning for Large Language Models

Philipp Becker, Niklas Freymuth, Serge Thilges, Fabian Otto, Gerhard Neumann
ArXiv

Model-free Reinforcement Learning

TROLL: Trust Regions improve Reinforcement Learning for Large Language Models

Philipp Becker, Niklas Freymuth, Serge Thilges, Fabian Otto, Gerhard Neumann
ArXiv

Back to Top ↑