Calibrated Test-Time Guidance for Bayesian Inference

Researchers have identified flaws in existing test-time guidance methods for diffusion models that prevent proper Bayesian posterior sampling. They propose new estimators that enable calibrated inference, significantly outperforming previous methods on Bayesian tasks and matching state-of-the-art results in black hole image reconstruction.