Loop corrections for message passing algorithms in continuous variable models

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dc.creatorWemmenhove, Bastian
dc.creatorKappen, Bert
dc.date2007-05-31
dc.date.accessioned2026-07-07T08:03:42Z
dc.date.available2026-07-07T08:03:42Z
dc.descriptionIn this paper we derive the equations for Loop Corrected Belief Propagation on a continuous variable Gaussian model. Using the exactness of the averages for belief propagation for Gaussian models, a different way of obtaining the covariances is found, based on Belief Propagation on cavity graphs. We discuss the relation of this loop correction algorithm to Expectation Propagation algorithms for the case in which the model is no longer Gaussian, but slightly perturbed by nonlinear terms.
dc.identifierhttps://arxiv.org/abs/0705.4566
dc.identifierhttp://arxiv.org/abs/0705.4566
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/129677
dc.subjectArtificial Intelligence
dc.subjectMachine Learning
dc.titleLoop corrections for message passing algorithms in continuous variable models
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