Outlier-robust Diffusion Posterior Sampling for Bayesian Inverse Problems
arXiv:2602.02045v2 Announce Type: replace
Abstract: Diffusion models have emerged as powerful learned priors for Bayesian inverse problems (BIPs). Diffusion-based solvers rely on a presumed likelihood for the observations in BIPs to guide the generati…