GANs for LIFE: Generative Adversarial Networks for Likelihood Free Inference

Vinay Jethava, Devdatt P. Dubhashi

Abstract: We introduce a framework using Generative Adversarial Networks (GANs) for likelihood--free inference (LFI) and Approximate Bayesian Computation (ABC) where we replace the black-box simulator model with an approximator network and generate a rich set of summary features in a data driven fashion. On benchmark data sets, our approach improves on others with respect to scalability, ability to handle high dimensional data and complex probability distributions.