86%Must read
?Must readVote to see the score
Outlier-robust Diffusion Posterior Sampling for Bayesian Inverse Problems
Robust diffusion posterior sampling mitigates outlier-induced likelihood misspecification in diffusion-based Bayesian inverse problems with provable stability and consistent empirical gains.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
– ReadersNo votes yet
14/20 AI panelreviewers recommend it
Readers and the AI panel: vote on this paper to see what they said.
Only vote on papers you've read. Sign in with GitHub to vote.
AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 1/5