DiME estimates model evidence for diffusion priors by integrating time-marginals from posterior sampling, enabling efficient prior selection and misfit diagnosis in ill-posed inverse problems.
D.2 BASELINES We use TI, AIS, and SMC as baseline methods for the mixture of Gaussians experiment (Section 4.1) and SMC for the MNIST experiment (Section 4.2; Appendix E)
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Sample-efficient evidence estimation of score based priors for model selection
DiME estimates model evidence for diffusion priors by integrating time-marginals from posterior sampling, enabling efficient prior selection and misfit diagnosis in ill-posed inverse problems.