About: Probabilistic Inference in BN2T Models by Weighted Model Counting

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Exact inference in Bayesian networks with nodes having a large parent set is not tractable using standard techniques as are the junction tree method or the variable elimination. However, in many applications, the conditional probability tbles of these nodes have certain local structure than can be exploited to make the exact inference tractable. In this paper we combine the CP tensor decomposition of probability tables with probabilistic inference using weighted model counting. The motivation for this combination is to exploit not only the local structure of some conditional probability tables but also other structural information potentialy present in the Baysian network, like determinism or context specific independence. We illustrate the proposed combination on BN2T networks -- two-layered Bayesian networks with conditional probability tables representing noisy threshold models. Exact inference in Bayesian networks with nodes having a large parent set is not tractable using standard techniques as are the junction tree method or the variable elimination. However, in many applications, the conditional probability tbles of these nodes have certain local structure than can be exploited to make the exact inference tractable. In this paper we combine the CP tensor decomposition of probability tables with probabilistic inference using weighted model counting. The motivation for this combination is to exploit not only the local structure of some conditional probability tables but also other structural information potentialy present in the Baysian network, like determinism or context specific independence. We illustrate the proposed combination on BN2T networks -- two-layered Bayesian networks with conditional probability tables representing noisy threshold models. (en)
Title	Probabilistic Inference in BN2T Models by Weighted Model Counting Probabilistic Inference in BN2T Models by Weighted Model Counting (en)
skos:prefLabel	Probabilistic Inference in BN2T Models by Weighted Model Counting Probabilistic Inference in BN2T Models by Weighted Model Counting (en)
skos:notation	RIV/67985556:_____/13:00399130!RIV14-GA0-67985556
http://linked.open...avai/predkladatel	Ústav teorie informace a automatizace AV ČR, v. v. i.
http://linked.open...avai/riv/aktivita	I P
http://linked.open...avai/riv/aktivity	I, P(GA102/09/1278), P(GA13-20012S)
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Tichavský, Petr Vomlel, Jiří
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Ústav teorie informace a automatizace AV ČR, v. v. i.
http://linked.open...dnocenehoVysledku	99659
http://linked.open...ai/riv/idVysledku	RIV/67985556:_____/13:00399130
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Bayesian networks; Models of Independence of causal influence; Noisy threshold models; Probabilistic inference; Weighted model counting; Arithmetic circuits (en)
http://linked.open.../riv/klicoveSlovo	Arithmetic circuits Models of Independence of causal influence Noisy threshold models Weighted model counting Probabilistic inference Bayesian networks
http://linked.open...ontrolniKodProRIV	[D7EB1130949B]
http://linked.open...v/mistoKonaniAkce	Aalborg
http://linked.open...i/riv/mistoVydani	Amsterdam
http://linked.open...i/riv/nazevZdroje	Proceedings of the Twelfth Scandinavian Conference on Artificial Intelligence
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...vavai/riv/projekt	Conditional independence structures: algebraic and geometric methods Advanced methods of blind source separation and blind deconvolution
http://linked.open...UplatneniVysledku	2013
http://linked.open...iv/tvurceVysledku	Tichavský, Petr Vomlel, Jiří
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2013-11-20 (xsd:date)
number of pages	10 (xsd:int)
http://bibframe.org/vocab/doi	10.3233/978-1-61499-330-8-275
http://purl.org/ne...btex#hasPublisher	IOS Press
https://schema.org/isbn	978-1-61499-329-2

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