Dynamic Bayesian network

Known as: DBN, Dynamic Bayesian networks, Dynamical Bayesian network 
A Dynamic Bayesian Network (DBN) is a Bayesian network which relates variables to each other over adjacent time steps. This is often called a Two… (More)
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Papers overview

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Highly Cited
2010
Highly Cited
2010
Learning dynamic Bayesian network structures provides a pr inci led mechanism for identifying conditional dependencies in time… (More)
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Highly Cited
2009
Highly Cited
2009
As with any application of machine learning, web search ranking requires labeled data. The labels usually come in the form of… (More)
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Highly Cited
2009
Highly Cited
2009
Directed graphical models such as Bayesian networks are a favored formalism for modeling the dependency structures in complex… (More)
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Highly Cited
2008
Highly Cited
2008
Given the increasing dependence of our societies on networked information systems, the overall security of these systems should… (More)
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Highly Cited
2004
Highly Cited
2004
MOTIVATION Network inference algorithms are powerful computational tools for identifying putative causal interactions among… (More)
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Highly Cited
2003
Highly Cited
2003
This article deals with the identification of gene regulatory networks from experimental data using a statistical machine… (More)
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Highly Cited
2003
Highly Cited
2003
MOTIVATION Bayesian networks have been applied to infer genetic regulatory interactions from microarray gene expression data… (More)
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Highly Cited
2002
Highly Cited
2002
Dynamic Bayesian Networks: Representation, Inference and Learning by Kevin Patrick Murphy Doctor of Philosophy in Computer… (More)
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Highly Cited
2002
Highly Cited
2002
Chapter ?? introduced hidden Markov models (HMMs), and Chapter ?? introduced state space models (SSMs), both of which are popular… (More)
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Highly Cited
2000
Highly Cited
2000
Particle filters (PFs) are powerful sampling­ based inference/learning algorithms for dynamic Bayesian networks (DBNs). They… (More)
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