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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… 
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Related topics

Related topics

50 relations
Abductive reasoningArtificial IntelligenceBayesian programmingBioinformatics

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2010
Highly Cited
2010
Using Bayesian networks for cyber security analysis
Capturing the uncertain aspects in cyber security is important for security analysis in enterprise networks. However, there has… 
Highly Cited
2010
Highly Cited
2010
Bayesian Artificial Intelligence, Second Edition
Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the… 
Review
2006
Review
2006
Bayesian belief networks: applications in ecology and natural resource management
In this introduction to the following series of papers on Bayesian belief networks (BBNs) we briefly summarize BBNs, review their… 
Highly Cited
2004
Highly Cited
2004
Bayesian Networks for Data Mining
A Bayesian network is a graphical model that encodesprobabilistic relationships among variables of interest. When used… 
Highly Cited
2004
Highly Cited
2004
Bayesian Networks in Reliability: Some Recent Developments
In this talk I will introduce the basic properties of Bayesian network models, and discuss why BN models are well suited for… 
Highly Cited
2003
Highly Cited
2003
A Bayesian network framework for relational shape matching
A Bayesian network formulation for relational shape matching is presented. The main advantage of the relational shape matching… 
Highly Cited
1999
Highly Cited
1999
Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithm
Learning Bayesian networks is often cast as an optimization problem, where the computational task is to find a structure that… 
Highly Cited
1998
Highly Cited
1998
Bayesian Inference on Network Traffic Using Link Count Data
Abstract We study Bayesian models and methods for analysing network traffic counts in problems of inference about the traffic… 
Highly Cited
1995
Highly Cited
1995
Bayesian Learning for Neural Networks
Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions… 
Review
1995
Review
1995
Learning Bayesian Networks: Search Methods and Experimental Results
We discuss Bayesian approaches for learning Bayesian networks from data. First, we review a metric for computing the relative… 
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