Author

Tianao Li

Northwestern university

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Preprint Sep 2026

FlowSGS: Improving Flow Priors for Inverse Imaging with Stochastic Interpolants

Flow matching has emerged as the state-of-the-art generative model and has been used for plug-and-play (PnP) priors to solve inverse problems in computational imaging. However, existing flow-based inverse solvers make simplifying approximations in posterior sampling and/or assume linear forward models. In contrast, pri...

Tianao Li, Xin-Hui Qian, Emma Alexander · 0 citations

Preprint Sep 2026

FlowSGS: Improving Flow Matching Priors for Inverse Imaging with Stochastic Interpolants

This work introduces FlowSGS, a flow-based posterior sampling method using Split Gibbs Sampling (SGS) to decompose the posterior into a likelihood step and a prior step and provides a form for the prior step that uses SI's reverse-time SDE, and shows connections to previous PnP methods.

Tianao Li, Xin-Hui Qian, Emma Alexander · 0 citations