Inference by belief propagation in composite systems

Etienne Mallard, David Saad

Research output: Contribution to journalArticle

Abstract

We devise a message passing algorithm for probabilistic inference in composite systems, consisting of a large number of variables, that exhibit weak random interactions among all variables and strong interactions with a small subset of randomly chosen variables; the relative strength of the two interactions is controlled by a free parameter. We examine the performance of the algorithm numerically on a number of systems of this type for varying mixing parameter values.
Original languageEnglish
Article number021107
Pages (from-to)021107
Number of pages1
JournalPhysical Review E
Volume78
Issue number2
DOIs
Publication statusPublished - 8 Aug 2008

Bibliographical note

©2008 The American Physical Society

Keywords

  • message passing algorithm
  • probabilistic inference
  • composite systems
  • variables
  • interactions

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