Publications

PointMapPolicy: Structured Point Cloud Processing for Multi-Modal Imitation Learning
Jia, X.; Wang, Q.; Wang, A.; Wang, H. A.; Gyenes, B.; Gospodinov, E.; Jiang, X.; Li, G.; Zhou, H.; Liao, W.; Huang, X.; Beck, M.; Reuss, M.; Lioutikov, R.; Neumann, G.
2025. arxiv. doi:10.48550/arXiv.2510.20406 

PointMapPolicy: Structured Point Cloud Processing for Multi-Modal Imitation Learning
Jia, X.; Wang, Q.; Wang, A.; Wang, H. A.; Gyenes, B.; Gospodinov, E.; Jiang, X.; Li, G.; Zhou, H.; Liao, W.; Huang, X.; Beck, M.; Reuss, M.; Lioutikov, R.; Neumann, G.
2025. The Thirty-ninth Annual Conference on Neural Information Processing Systems; San Diego, USA, 02.-07.12.2025, 30 S 

Scaling Robot Policy Learning via Zero-Shot Labeling with Foundation Models
Blank, N.; Reuss, M.; Rühle, M.; Yagmurlu, Ö. E.; Wenzel, F.; Mees, O.; Lioutikov, R.
2024. Proceedings of the 8th Conference on Robot Learning. Ed.: P. Agrawal, 4158 – 4187, Machine Learning Research Press (ML Research Press)

Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrations
Jia, X.; Blessing, D.; Jiang, X.; Reuss, M.; Donat, A.; Lioutikov, R.; Neumann, G.
2024. The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024, OpenReview.net

Multimodal Diffusion Transformer: Learning Versatile Behavior from Multimodal Goals
Reuss, M.; Yağmurlu, Ö. E.; Wenzel, F.; Lioutikov, R.
2024. Robotics: Science and Systems XX. Ed.: D. Kulic, Robotics: Science and Systems Foundation 

Information Maximizing Curriculum: A Curriculum-Based Approach for Learning Versatile Skills
Blessing, D.; Celik, O.; Jia, X.; Reuss, M.; Li, M.; Lioutikov, R.; Neumann, G.
2024. Advances in Neural Information Processing Systems. Ed.: A. Oh, MIT-Press

Goal-Conditioned Imitation Learning using Score-based Diffusion Policies
Reuss, M.; Li, M.; Jia, X.; Lioutikov, R.
2023. arxiv. doi:10.48550/arXiv.2304.02532 

Information Maximizing Curriculum: A Curriculum-Based Approach for Training Mixtures of Experts
Blessing, D.; Celik, O.; Jia, X.; Reuss, M.; Li, M. X.; Lioutikov, R.; Neumann, G.
2023. arxiv. doi:10.48550/arXiv.2303.15349 

End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control
Reuss, M.; Duijkeren, N. van; Krug, R.; Becker, P.; Shaj, V.; Neumann, G.
2022. Robotics: Science and Systems XVIII. Ed.: K. Hauser. doi:10.48550/arXiv.2205.13804