Learning few-step posterior samplers by unfolding and distillation of diffusion models

Charlesquin Kemajou Mbakam, Jonathan Spence, Marcelo Pereyra

Diffusion models (DMs) have emerged as powerful image priors in Bayesian computational imaging. Two primary strategies have been proposed for leveraging DMs in this context: Plug-a…