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BayesFP: Posterior Estimation for Flow-Based Policies via Feynman-Kac Sampling
Robots must generate trajectories that remain faithful to learned expert behavior while satisfying safety constraints and task-specific objectives specified only at inference time. We formulate constrained trajectory generation for pretrained diffusion and flow-matching policies as Bayesian posterio
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