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Variational Predictive Information Bottleneck (1910.10831v1)

Published 23 Oct 2019 in cs.LG, cs.IT, math.IT, and stat.ML

Abstract: In classic papers, Zellner demonstrated that Bayesian inference could be derived as the solution to an information theoretic functional. Below we derive a generalized form of this functional as a variational lower bound of a predictive information bottleneck objective. This generalized functional encompasses most modern inference procedures and suggests novel ones.

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