3 papers
cs.LG2026
Manifold Sampling via Entropy Maximization
Cornelius V. Braun, Tilman Burghoff, Marc Toussaint
Sampling from constrained distributions has a wide range of applications, including in Bayesian optimization and robotics. Prior work establishes convergence and feasibility guaran…
cs.RO2026
Stability-Guided Exploration for Diverse Motion Generation
Eckart Cobo-Briesewitz, Tilman Burghoff, Denis Shcherba +2
Scaling up datasets is highly effective in improving the performance of deep learning models, including in the field of robot learning. However, data collection still proves to be…
cs.RO2026
Combining Constrained Sampling and Reinforcement Learning for Manipulation
Marc Toussaint, Cornelius V. Braun, Armand Jordana +5
Training manipulation policies in contact-rich settings is a core challenge in robotics. While Reinforcement Learning (RL) has demonstrated its strength in such settings, it may st…