AI RESEARCH

Manifold Sampling via Entropy Maximization

arXiv CS.AI

ArXi:2605.12338v1 Announce Type: cross Sampling from constrained distributions has a wide range of applications, including in Bayesian optimization and robotics. Prior work establishes convergence and feasibility guarantees for constrained sampling, but assumes that the feasible set is connected. However, in practice, the feasible set often decomposes into multiple disconnected components, which makes efficient sampling under constraints challenging.