Optimal experimental design for infinite-dimensional Bayesian inverse problems governed by PDEs: a review

Abstract We present a review of methods for optimal experimental design (OED) Bayesian inverse problems governed by partial differential equations with infinite-dimensional parameters. The focus is on where one seeks to optimize the placement measurement points, at which data are collected, such that uncertainty in estimated parameters minimized. mathematical foundations OED this context and survey computational class under study. also outline some directions future research area.