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Adversarial Variational Optimization of Non-Differentiable Simulators
Louppe, Gilles; Hermans, Joeri; Cranmer, Kyle
2019In Proceedings of Machine Learning Research
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Keywords :
Statistics - Machine Learning; Computer Science - Learning
Abstract :
[en] Complex computer simulators are increasingly used across fields of science as generative models tying parameters of an underlying theory to experimental observations. Inference in this setup is often difficult, as simulators rarely admit a tractable density or likelihood function. We introduce Adversarial Variational Optimization (AVO), a likelihood-free inference algorithm for fitting a non-differentiable generative model incorporating ideas from generative adversarial networks, variational optimization and empirical Bayes. We adapt the training procedure of Wasserstein GANs by replacing the differentiable generative network with a domain-specific simulator. We solve the resulting non-differentiable minimax problem by minimizing variational upper bounds of the two adversarial objectives. Effectively, the procedure results in learning a proposal distribution over simulator parameters, such that the Wasserstein distance between the marginal distribution of the synthetic data and the empirical distribution of observed data is minimized. We present results of the method with simulators producing both discrete and continuous data.
Disciplines :
Computer science
Author, co-author :
Louppe, Gilles  ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Big Data
Hermans, Joeri ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Big Data
Cranmer, Kyle
Language :
English
Title :
Adversarial Variational Optimization of Non-Differentiable Simulators
Publication date :
April 2019
Event name :
AISTATS 2019
Event place :
Okinawa, Japan
Event date :
April 16-18, 2019
Audience :
International
Journal title :
Proceedings of Machine Learning Research
eISSN :
2640-3498
Publisher :
Microtome Publishing, Brookline, United States - Massachusetts
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 28 June 2018

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