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NIPS
2008
13 years 11 months ago
Learning Bounded Treewidth Bayesian Networks
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...
Gal Elidan, Stephen Gould
UAI
2003
13 years 11 months ago
Learning Continuous Time Bayesian Networks
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
Uri Nodelman, Christian R. Shelton, Daphne Koller
PE
2010
Springer
170views Optimization» more  PE 2010»
13 years 8 months ago
Approximating passage time distributions in queueing models by Bayesian expansion
We introduce Bayesian Expansion (BE), an approximate numerical technique for passage time distribution analysis in queueing networks. BE uses a class of Bayesian networks to appro...
Giuliano Casale
ECSQARU
2005
Springer
14 years 3 months ago
Hydrologic Models for Emergency Decision Support Using Bayesian Networks
In the presence of a river flood, operators in charge of control must take decisions based on imperfect and incomplete sources of information (e.g., data provided by a limited numb...
Martín Molina, Raquel Fuentetaja, Luis Garr...
IJRR
2006
183views more  IJRR 2006»
13 years 10 months ago
Bayesian Occupancy Filtering for Multitarget Tracking: An Automotive Application
Reliable and efficient perception and reasoning in dynamic and densely cluttered environments are still major challenges for driver assistance systems. Most of today's system...
Christophe Coué, Cédric Pradalier, C...