Optimal Experimental Design for Bayesian Inverse Problems Governed by PDEs: A Review
Alen Alexanderian · arXiv (Cornell University) · 2020
We present a review of methods for optimal experimental design (OED) for Bayesian inverse problems governed by partial differential equations. The focus is on large-scale inverse problems with infinite-dimensional parameters. We present the mathematical foundations of OED in this context and survey the computational methods for the class of OED problems under study. We also outline some directions for future research in this area.