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Easy High-Dimensional Likelihood-Free Inference (1711.11139v2)

Published 29 Nov 2017 in cs.LG and stat.ML

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.

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