no code implementations • 15 Feb 2020 • Johnathan Bardsley, Tiangang Cui
In this work, we aim to develop scalable optimization-based Markov chain Monte Carlo (MCMC) methods for solving hierarchical Bayesian inverse problems with nonlinear parameter-to-observable maps and a broader class of hyperparameters.