Closed-Form Diffusion Policies enable training-free imitation learning by using closed-form scores derived from demonstration data, achieving competitive benchmark performance with millisecond inference and composable editing of pre-trained policies.
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GLENS uses diffusion models on solver iterates to generate high-quality and diverse initial guesses for multimodal non-convex optimization, leading to faster solver convergence.
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Training-Free Imitation Learning with Closed-Form Diffusion Policies
Closed-Form Diffusion Policies enable training-free imitation learning by using closed-form scores derived from demonstration data, achieving competitive benchmark performance with millisecond inference and composable editing of pre-trained policies.