0399130 20240103203310.120140304235959.9 84894653353 000343477100029 10.3233/978-1-61499-330-8-275 10 s. P cav_un_epca*0399129978-1-61499-329-2275-284AmsterdamIOS Press2013JaegerManfredNielsenThomas DyhreViappianiPaolo Bayesian networks Models of Independence of causal influence Noisy threshold models Probabilistic inference Weighted model counting Arithmetic circuits cav_un_auth*0101228 Matematická teorie rozhodování Department of Decision Making Theory MTR MTR Department of Decision Making Theory Vomlel Jiří UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101212 Stochastická informatika Department of Stochastic Informatics SI SI Department of Stochastic Informatics Tichavský Petr UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2013/MTR/vomlel-0399130.pdf cav_un_auth*0292670 GA13-20012S GA ČR cav_un_auth*0253174 GA102/09/1278 GA ČR 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. cav_un_auth*0301481 The Scandinavian Conference on Artificial Intelligence (SCAI 2013) /12./ 20.11.2013-22.11.2013 Aalborg DK JD 2014 2 PR RVO:67985556 http://hdl.handle.net/11104/0228479 S 2013 84894653353 SCOPUS 000343477100029 WOS cav_un_epca*0399129 Proceedings of the Twelfth Scandinavian Conference on Artificial Intelligence 978-1-61499-329-2 275 284 Amsterdam IOS Press 2013 Frontiers in Artificial Intelligence and Applications Jaeger Manfred 340 Nielsen Thomas Dyhre 340 Viappiani Paolo 340