Kavli Affiliate: Matthew Fisher | Summary:Bayesian inference is optimal when the statistical model is well-specified, while outside this setting Bayesian inference can catastrophically fail; accordingly a wealth of post-Bayesian methodologies have been proposed. Predictively oriented (PrO) approaches lift the statistical model $P_θ$ to an (infinite) mixture model $int P_θ; mathrmdQ(θ)$ and fit this predictive distribution […]
Continue.. Detecting Model Misspecification in Bayesian Inverse Problems via Variational Gradient Descent