Denis Blessing

According to our database, Denis Blessing authored at least 22 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Bridge Matching Sampler: Scalable Sampling via Generalized Fixed-Point Diffusion Matching.

Denis Blessing, Lorenz Richter, Julius Berner, Egor Malitskiy, Gerhard Neumann

CoRR, March, 2026

2025

Learning Boltzmann Generators via Constrained Mass Transport.

Christopher von Klitzing, Denis Blessing, Henrik Schopmans, Pascal Friederich, Gerhard Neumann

CoRR, October, 2025

MaNGO - Adaptable Graph Network Simulators via Meta-Learning.

Philipp Dahlinger, Tai Hoang, Denis Blessing, Niklas Freymuth, Gerhard Neumann

CoRR, October, 2025

Trust Region Constrained Measure Transport in Path Space for Stochastic Optimal Control and Inference.

Denis Blessing, Julius Berner, Lorenz Richter, Carles Domingo-Enrich, Yuanqi Du, Arash Vahdat, Gerhard Neumann

CoRR, August, 2025

Scaffolding Dexterous Manipulation with Vision-Language Models.

Vincent de Bakker, Joey Hejna, Tyler Ga Wei Lum, Onur Celik, Aleksandar Taranovic, Denis Blessing, Gerhard Neumann, Jeannette Bohg, Dorsa Sadigh

CoRR, June, 2025

X-IL: Exploring the Design Space of Imitation Learning Policies.

Xiaogang Jia, Atalay Donat, Xi Huang, Xuan Zhao, Denis Blessing, Hongyi Zhou, Han A. Wang, Hanyi Zhang, Qian Wang, Rudolf Lioutikov, Gerhard Neumann

CoRR, February, 2025

Towards Fusing Point Cloud and Visual Representations for Imitation Learning.

Atalay Donat, Xiaogang Jia, Xi Huang, Aleksandar Taranovic, Denis Blessing, Ge Li, Hongyi Zhou, Hanyi Zhang, Rudolf Lioutikov, Gerhard Neumann

CoRR, February, 2025

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning.

Onur Celik, Zechu Li, Denis Blessing, Ge Li, Daniel Palanicek, Jan Peters, Georgia Chalvatzaki, Gerhard Neumann

CoRR, February, 2025

DIME: Diffusion-Based Maximum Entropy Reinforcement Learning.

Onur Celik, Zechu Li, Denis Blessing, Ge Li, Daniel Palenicek, Jan Peters, Georgia Chalvatzaki, Gerhard Neumann

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Sequential Controlled Langevin Diffusions.

Junhua Chen, Lorenz Richter, Julius Berner, Denis Blessing, Gerhard Neumann, Anima Anandkumar

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

End-to-end Learning of Gaussian Mixture Priors for Diffusion Sampler.

Denis Blessing, Xiaogang Jia, Gerhard Neumann

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Underdamped Diffusion Bridges with Applications to Sampling.

Denis Blessing, Julius Berner, Lorenz Richter, Gerhard Neumann

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

MaIL: Improving Imitation Learning with Mamba.

Xiaogang Jia, Qian Wang, Atalay Donat, Bowen Xing, Ge Li, Hongyi Zhou, Onur Celik, Denis Blessing, Rudolf Lioutikov, Gerhard Neumann

CoRR, 2024

Variational Distillation of Diffusion Policies into Mixture of Experts.

Hongyi Zhou, Denis Blessing, Ge Li, Onur Celik, Xiaogang Jia, Gerhard Neumann, Rudolf Lioutikov

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling.

Denis Blessing, Xiaogang Jia, Johannes Esslinger, Francisco Vargas, Gerhard Neumann

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrations.

Xiaogang Jia, Denis Blessing, Xinkai Jiang, Moritz Reuss, Atalay Donat, Rudolf Lioutikov, Gerhard Neumann

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Transport meets Variational Inference: Controlled Monte Carlo Diffusions.

Francisco Vargas, Shreyas Padhy, Denis Blessing, Nikolas Nüsken

Proceedings of the Twelfth International Conference on Learning Representations, 2024

MaIL: Improving Imitation Learning with Selective State Space Models.

Xiaogang Jia, Qian Wang, Atalay Donat, Bowen Xing, Ge Li, Hongyi Zhou, Onur Celik, Denis Blessing, Rudolf Lioutikov, Gerhard Neumann

Proceedings of the Conference on Robot Learning, 6-9 November 2024, Munich, Germany., 2024

2023

Information Maximizing Curriculum: A Curriculum-Based Approach for Training Mixtures of Experts.

Denis Blessing, Onur Celik, Xiaogang Jia, Moritz Reuss, Maximilian Xiling Li, Rudolf Lioutikov, Gerhard Neumann

CoRR, 2023

Information Maximizing Curriculum: A Curriculum-Based Approach for Learning Versatile Skills.

Denis Blessing, Onur Celik, Xiaogang Jia, Moritz Reuss, Maximilian Xiling Li, Rudolf Lioutikov, Gerhard Neumann

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Curriculum-Based Imitation of Versatile Skills.

Maximilian Xiling Li, Onur Celik, Philipp Becker, Denis Blessing, Rudolf Lioutikov, Gerhard Neumann

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2018

EmbryoMiner: A new framework for interactive knowledge discovery in large-scale cell tracking data of developing embryos.

Benjamin Schott, Manuel Traub, Cornelia Schlagenhauf, Masanari Takamiya, Thomas Antritter, Andreas Bartschat, Katharina Löffler, Denis Blessing, Jens C. Otte, Andrei Kobitski, G. Ulrich Nienhaus, Uwe Strähle, Ralf Mikut, Johannes Stegmaier

PLoS Comput. Biol., 2018