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stat.ME2025
Detecting Model Misspecification in Bayesian Inverse Problems via Variational Gradient Descent
Qingyang Liu, Matthew A. Fisher, Zheyang Shen +4
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-Ba…
stat.CO2025
Extrapolation of Tempered Posteriors
Mengxin Xi, Zheyang Shen, Marina Riabiz +2
Tempering is a popular tool in Bayesian computation, being used to transform a posterior distribution into a reference distribution that is more easily approximated. Se…
stat.CO2025
A Computable Measure of Suboptimality for Entropy-Regularised Variational Objectives
Clémentine Chazal, Heishiro Kanagawa, Zheyang Shen +2
Several methods in statistics and machine learning target a probability distribution for which an entropy-regularised variational objective is minimised. This increased flexibility…