0410574 20240103182223.520060210235959.9 1-55860-709-9 Marginalization in composed probabilistic models San Francisco Morgan Kaufmann 2000 8 s. Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence36-43BoutilierC.GoldszmidtM. multidimensional distribution Bayesian network computation cav_un_auth*0101118 Jiroušek Radim UTIA-B Department of Decision Making Theory Ústav teorie informace a automatizace AV ČR, v. v. i. 120 GA201/98/1487 GA ČR cav_un_auth*0005923 VS96008 GA MŠk cav_un_auth*0025049 AV0Z1075907 Composition of low-dimensional distributions, whose foundations were laid in the paper published in the Proceedings of UAI'97, appeared to be an alternative apparatus to describe multidimensional probabilistic models. In contrast to Graphical Markov Models, which define multidimensional distributions in a declarative way, this approach is rather procedural. cav_un_auth*0212764 Conference on Uncertainty in Artificial Intelligence /16./ Stanford US 30.06.2000-03.07.2000 BA MTR http://hdl.handle.net/11104/0130663 UTIA-B 20010043 2000 2000 San Francisco Morgan Kaufmann 1-55860-709-9 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence 36 43 Boutilier C. 340 Goldszmidt M. 340