Generalized Belief Propagation


Belief propagation (BP) was only supposed to work for tree-like networks but works surprisingly well in many applications involving networks with loops, including turbo codes. However, there has been little understanding of the algorithm or the nature of the solutions it finds for general graphs. We show that BP can only converge to a stationary point of an approximate free energy, known as the Bethe free energy in statistical physics. This result characterizes BP fixed-points and makes connections with variational approaches to approximate inference. More importantly, our analysis lets us build on the progress made in statistical physics since Bethe's approximation was introduced in 1935. Kikuchi and others have shown how to construct more accurate free energy approximations, of which Bethe's approximation is the simplest. Exploiting the insights from our analysis, we derive generalized belief propagation (GBP) versions of these Kikuchi approximations. These new message passing algorithms can be significantly more accurate than ordinary BP, at an adjustable increase in complexity. We illustrate such a new GBP algorithm on a grid Markov network and show that it gives much more accurate marginal probabilities than those found using ordinary BP. This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Information Technology Center America; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Information Technology Center America. All rights reserved.

Extracted Key Phrases

Showing 1-3 of 3 references

Cluster variation method of cooperative phenomena and T. Morita: Cluster variation method of cooperative phenomena and its its generalization I

  • T Morita
  • 1957

A theory of cooperative phenomena, Phys. Rev., R. Kikuchi: A theory of cooperative phenomena

  • R Kikuchi
  • 1951

Extension of Belief Propagation Extension of Belief Propagation Generalized Belief Propagation Generalized Belief Propagation

Showing 1-10 of 614 extracted citations
Citations per Year

1,030 Citations

Semantic Scholar estimates that this publication has received between 901 and 1,179 citations based on the available data.

See our FAQ for additional information.