Georgia Institute of Technology College of Sciences

I will begin by introducing the concept of path Radon–Nikodym derivative (path RND) and explaining how it connects to, and accelerates, classical sampling and estimation algorithms such as parallel tempering and free-energy perturbation. I will then show how path RND offers a unifying perspective on controlling diffusion models using Sequential Monte Carlo. Finally, I will present a new paradigm for inference-time control based on parallel tempering, which enables more robust manipulation of diffusion trajectories.