Inference by belief propagation in composite systems

Etienne Mallard, David Saad

    Research output: Contribution to journalArticlepeer-review


    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
    Issue number2
    Publication statusPublished - 8 Aug 2008

    Bibliographical note

    ©2008 The American Physical Society


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


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