3 papers
cs.LG2025
Saving Foundation Flow-Matching Priors for Inverse Problems
Yuxiang Wan, Ryan Devera, Wenjie Zhang +1
Foundation flow-matching (FM) models promise universal priors for solving inverse problems (IPs); yet today, they trail behind domain-specific and even untrained priors. \emph{How…
eess.IV2025
FMPlug: Plug-In Foundation Flow-Matching Priors for Inverse Problems
Yuxiang Wan, Ryan Devera, Wenjie Zhang +1
We present FMPlug, a novel plug-in framework that enhances foundation flow-matching (FM) priors for solving ill-posed inverse problems. Unlike traditional approaches that rely on d…
eess.SP2024
What is Wrong with End-to-End Learning for Phase Retrieval?
Wenjie Zhang, Yuxiang Wan, Zhong Zhuang +1
For nonlinear inverse problems that are prevalent in imaging science, symmetries in the forward model are common. When data-driven deep learning approaches are used to solve such p…