Easy High-Dimensional Likelihood-Free Inference
Machine Learning
2018-08-24 v2 Machine Learning
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.
Cite
@article{arxiv.1711.11139,
title = {Easy High-Dimensional Likelihood-Free Inference},
author = {Vinay Jethava and Devdatt Dubhashi},
journal= {arXiv preprint arXiv:1711.11139},
year = {2018}
}