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Introduction to MASEM (Manifold Sampling via Entropy Maximization)
Published:
This post is an introduction/explanation to the paper “Manifold Sampling via Entropy Maximization” by Cornelius V. Braun and myself as equal contributors under the supervision of Marc Toussaint [1], where we introduce a framework called MASEM. I will explain MASEM very informally; I recommend reading the paper (perhaps armed with the intuition gained here) for a rigorous treatment.
Hello World
Published:
This is going to be a very cool blog with relevant posts about robotics and stuff (I hope). Welcome, feel free to look around. If you have suggestions, don’t hesitate to contact me!
publications
Combined Constrained Sampling and Reinforcement Learning for Robotic Manipulation
Marc Toussaint, Cornelius V. Braun, Armand Jordana, Sayantan Auddy, Eckart Cobo-Briesewitz, Denis Shcherba, Tilman Burghoff, Justin Carpentier; 2026
tl;dr: CSRL uses constrained sampling to guide reinforcement learning towards diverse manipulation strategies.
Under Review
Stability-Guided Exploration for Diverse Motion Generation
Eckart Cobo-Briesewitz, Tilman Burghoff, Denis Shcherba, Armand Jordana, Marc Toussaint; 2026
tl;dr: The method (StaGE) generates diverse long-horizon manipulations by leveraging black-box simulation.
Under Review, Presented at ICRA Xplore Workshop 2026 (Oral)
Manifold Sampling via Entropy Maximization
Cornelius V. Braun*, Tilman Burghoff*, Marc Toussaint; 2026
tl;dr: Sampling from disconnected manifolds is hard; we tackle it with an entropy-maximizing resampling strategy called MASEM.
Under Review
