Bayesian network

Known as: Bayesian belief network, Belief networks, Bayes net 
A Bayesian network, Bayes network, belief network, Bayes(ian) model or probabilistic directed acyclic graphical model is a probabilistic graphical… (More)
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Papers overview

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Highly Cited
2009
Highly Cited
2009
This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides… (More)
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Highly Cited
2006
Highly Cited
2006
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines… (More)
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Highly Cited
2004
Highly Cited
2004
An algorithm, the bootstrap filter, is proposed for implementing recursive Bayesian filters. The required density of the state… (More)
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Highly Cited
2003
Highly Cited
2003
In many multivariate domains, we are interested in analyzing the dependency structure of the underlying distribution, e.g… (More)
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Highly Cited
1997
Highly Cited
1997
Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been… (More)
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Highly Cited
1996
Highly Cited
1996
A new method is proposed for exploiting causal independencies in exact Bayesian network inference. A Bayesian network can be… (More)
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Highly Cited
1996
Highly Cited
1996
Approaches to learning Bayesian networks from data typically combine a scoring metric with a heuristic search procedure. Given a… (More)
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Highly Cited
1996
Highly Cited
1996
Bayesiannetworks provide a languagefor qualitatively representing the conditional independence properties of a distribution. This… (More)
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Highly Cited
1993
Highly Cited
1993
This paper presents a simple framework for Horn clause abduc tion with probabilities associated with hypotheses The framework… (More)
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Highly Cited
1991
Highly Cited
1991
50 AI MAGAZINE u n d e r s t a n d i n g (Charniak and Goldman 1989a, 1989b; Goldman 1990), vision (Levitt, Mullin, and Binford… (More)
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