Markov Chain Generative Adversarial Neural Networks for Solving Bayesian Inverse Problems in Physics Applications

Nikolaj T. Mücke, Benjamin Sanderse, Sander Bohté +1

In the context of solving inverse problems for physics applications within a Bayesian framework, we present a new approach, Markov Chain Generative Adversarial Neural Networks (MCG…