Josie König

Dimension and model reduction approaches for linear Bayesian inverse problems with rank-deficient prior covariances

Abstract Bayesian inverse problems use observed data to update a prior probability distribution for an unknown state or parameter of a scientific system to a posterior distribution conditioned on the data. In many applications, the unknown parameter is high-dimensional, making co...