Solution of Physics-based Bayesian Inverse Problems with Deep Generative Priors

no code implementations • 6 Jul 2021 • Dhruv V Patel, Deep Ray, Assad A Oberai

Specifically, we demonstrate how using the approximate distribution learned by a Generative Adversarial Network (GAN) as a prior in a Bayesian update and reformulating the resulting inference problem in the low-dimensional latent space of the GAN, enables the efficient solution of large-scale Bayesian inverse problems.

Bayesian Inference Generative Adversarial Network +1

The Effect of Super-spreader Events in Epidemics

no code implementations • 3 Mar 2021 • Harisankar Ramaswamy, Assad A Oberai, Mitul Luhar, Yannis C Yortsos

The spread of infectious epidemics is often accelerated by super-spreader events.