Implicit Restoration Priors for Inverse Problems
Plug-and-play priors from pre-trained restoration networks
Pioneered a new class of plug-and-play priors by generalizing Regularization-by-Denoising (RED) to leverage any pre-trained image restoration network. Developed a suite of algorithms (DRP, ShaRP, ADOBI) for solving inverse problems using deterministic priors, stochastic priors, and diffusion bridge models. ICLR 2024, ICML 2025.