145 search results - page 14 / 29 » Bayesian Network Learning with Parameter Constraints |
106
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IJAR
2011
14 years 3 months ago
2011
The basic idea of an algebraic approach to learning Bayesian network (BN) structures is to represent every BN structure by a certain uniquely determined vector, called the standar...
IJAR
2010
14 years 10 months ago
2010
Bayesian networks with mixtures of truncated exponentials (MTEs) support efficient inference algorithms and provide a flexible way of modeling hybrid domains (domains containing ...
117
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BMCBI
2010
14 years 11 months ago
2010
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
105
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ENGL
2007
14 years 11 months ago
2007
—This paper details a learning decision-theoretic intelligent agent designed to solve the problem of guiding vehicles in the context of Personal Rapid Transit (PRT). The intellig...
124
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ICMCS
2008
IEEE
15 years 6 months ago
2008
IEEE
Several stochastic models provide an effective framework to identify the temporal structure of audiovisual data. Most of them need as input a first video structure, i.e. connecti...