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RECOMB
2004
Springer
16 years 6 months ago
Learning Regulatory Network Models that Represent Regulator States and Roles
Abstract. We present an approach to inferring probabilistic models of generegulatory networks that is intended to provide a more mechanistic representation of transcriptional regul...
Keith Noto, Mark Craven
KES
2007
Springer
16 years 2 days ago
Predictive and Contextual Feature Separation for Bayesian Metanetworks
Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of conditional dependency. However, dep...
Vagan Y. Terziyan
FLAIRS
2000
15 years 7 months ago
Independence Semantics for BKBs
Bayesian KnowledgeBases (BKB)are a rule-based probabilistic modelthat extend BayesNetworks(BN), by allowing context-sensitive independenceand cycles in the directed graph. BKBshav...
Solomon Eyal Shimony, Eugene Santos Jr., Tzachi Ro...
ICML
2010
IEEE
15 years 7 months ago
Probabilistic Backward and Forward Reasoning in Stochastic Relational Worlds
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...
Tobias Lang, Marc Toussaint
RECOMB
2003
Springer
16 years 6 months ago
Optimizing exact genetic linkage computations
Genetic linkage analysis is a challenging application which requires Bayesian networks consisting of thousands of vertices. Consequently, computing the likelihood of data, which i...
Dan Geiger, Maáyan Fishelson