  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.
