Show simple item record

dc.contributor.authorCobb, Barry R.
dc.contributor.authorShenoy, Prakash P.
dc.date.accessioned2006-04-13T18:31:17Z
dc.date.available2006-04-13T18:31:17Z
dc.date.issued2006-04
dc.identifier.citationCobb, B. R., and P. P. Shenoy, "Inference in hybrid Bayesian networks wih mixtures of truncated exponenials," International Journal of Approximate Reasoning, Vol. 41, No. 3, April 2006, pp. 257--286.
dc.identifier.issn0888-613X
dc.identifier.urihttp://hdl.handle.net/1808/902
dc.description.abstractMixtures of truncated exponentials (MTE) potentials are an alternative to discretization for solving hybrid Bayesian networks. Any probability density function (PDF) can be approximated with an MTE potential, which can always be marginalized in closed form. This allows propagation to be done exactly using the Shenoy-Shafer architecture for computing marginals, with no restrictions on the construction of a join tree. This paper presents MTE potentials that approximate an arbitrary normal PDF with any mean and a positive variance. The properties of these MTE potentials are presented, along with examples that demonstrate their use in solving hybrid Bayesian networks. Assuming that the joint density exists, MTE potentials can be used for inference in hybrid Bayesian networks that do not fit the restrictive assumptions of the conditional linear Gaussian (CLG) model, such as networks containing discrete nodes with continuous parents.
dc.format.extent570071 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherElsevier
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectHybrid Bayesian networks
dc.subjectMixtures of truncated exponentials
dc.subjectShenoy-Shafer architecture
dc.subjectConditional linear gaussian models
dc.titleInference in hybrid Bayesian networks wih mixtures of truncated exponenials
dc.typeArticle
dc.identifier.orcidhttps://orcid.org/0000-0002-8425-896X
dc.rights.accessrightsopenAccess


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Except where otherwise noted, this item's license is described as: This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.