Richard Wilkinson

Randomized Maximum Likelihood Via High-Dimensional Bayesian Optimization

Posterior sampling for high-dimensional Bayesian inverse problems is a common challenge in real-world applications. Randomized Maximum Likelihood (RML) is an optimization based methodology that gives samples from an approximation to the posterior distribution. We develop a high-dimensional Bayesian…