Unbiased Diffusion Variational Inversion via Principled Posterior Matching 事件

Unbiased Diffusion Variational Inversion via Principled Posterior Matching arXiv:2605.25042v1 Announce Type: new Abstract: Existing score-based methods for inverse problems often resort to approximate minimization of the KL divergence between the inversion distribution and the Bayesian posterior. Such an approximation leads to severe mode collapse and unreliable uncertainty quantification. In this paper, we propose Principled Posterior Matching (PPM), a framework that returns to the fundamental