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112
Voted
RECOMB
2004
Springer
16 years 22 days ago
2004
Springer
Abstract. We present an approach to inferring probabilistic models of generegulatory networks that is intended to provide a more mechanistic representation of transcriptional regul...
86
Voted
KES
2007
Springer
15 years 6 months ago
2007
Springer
Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of conditional dependency. However, dep...
104
Voted
FLAIRS
2000
15 years 1 months ago
2000
Bayesian KnowledgeBases (BKB)are a rule-based probabilistic modelthat extend BayesNetworks(BN), by allowing context-sensitive independenceand cycles in the directed graph. BKBshav...
127
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
Inference in graphical models has emerged as a promising technique for planning. A recent approach to decision-theoretic planning in relational domains uses forward inference in d...
103
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RECOMB
2003
Springer
16 years 22 days ago
2003
Springer
Genetic linkage analysis is a challenging application which requires Bayesian networks consisting of thousands of vertices. Consequently, computing the likelihood of data, which i...