Feedback control for sampling
Using particle feedback to help samplers approach a target probability distribution.
This project explores feedback control as a way to help particle samplers reach a target probability distribution. I investigate how density-level control laws can be implemented using particle observations, including when the target’s normalising constant is unknown. A central question is whether faster convergence translates into less computational work once the cost of the controller is included.