Learning to Replace MCMC in Split-Gibbs Diffusion Posterior Sampling via Deep Unfolding
DGX agentarXiv:2609.30539v1 Announce Type: cross Abstract: Split Gibbs sampling enables diffusion posterior inference for general nonlinear inverse problems by decoupling prior and likelihood computations, all