A Normalizing Flows based Difference-of-Entropies Estimator for Mutual Information

Haoran Ni, Martin Lotz

Keywords: Normalizing flows, mutual information, generative models

TL;DR: We present a new estimator for mutual information based on an implementation of the difference-of-entropies estimator using normalizing flows.

Abstract: Estimating Mutual Information (MI), a key measure of dependence of random quantities without specific modelling assumptions, is a challenging problem in high dimensions. We propose a novel mutual information estimator based on parametrizing conditional densities using normalizing flows, a deep generative model that has gained popularity in recent years. This estimator leverages a block autoregressive structure to achieve improved bias-variance trade-offs on standard benchmark tasks.

Primary Area: generative models

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Submission Number: 7013