Liang-Hao Cao

On Prior-to-Posterior Stability in the Wasserstein Metric for Bayesian Inverse Problems

Priors in Bayesian inverse problems are often approximated through discretization, hyperparameter estimation, or generative modeling. Understanding how prior approximation errors propagate to the posterior and subsequent predictions is therefore important. In this work, we study the stability of the prior-to-posterior...