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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
2019
Highly Cited
2019
Soft-Tempering Deep Belief Networks Parameters Through Genetic Programming
Deep neural networks have been widely fostered throughout the last years, primarily on account of their outstanding performance… 
Highly Cited
2009
Highly Cited
2009
Automatic tool for Alzheimer's disease diagnosis using PCA and Bayesian classification rules
An automatic tool to assist the interpretation of single photon emission computed tomography (SPECT) and positron emission… 
Highly Cited
2002
Highly Cited
2002
Correlation in an intrusion detection process
Generally, the intruder must perform several actions, organized in an intrusion scenario, to achieve his or her malicious… 
Highly Cited
2001
Highly Cited
2001
Color and Number Counts
We present near-IR (J and Ks) number counts and colors of galaxies detected in deep VLT-ISAAC images centered on the Chandra Deep… 
Highly Cited
1998
Highly Cited
1998
Spatial information retrieval from remote-sensing images. II. Gibbs-Markov random fields
For pt.I see ibid., p.1431-45 (1998). The authors present Gibbs-Markov random field (GMRF) models as a powerful and robust… 
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… 
Highly Cited
1995
Highly Cited
1995
Hierarchical Markovian Models: Symmetries and Reduction
  • P. Buchholz
  • Performance evaluation (Print)
  • 1995
  • Corpus ID: 12980518
Highly Cited
1995
Highly Cited
1995
A comparative study of speaker adaptation techniques
In previous work, we showed how to constrain the estimation of continuous mixture-density hidden Markov models (HMMs) when the… 
Highly Cited
1992
Highly Cited
1992
Bayesian Diagnosis in Expert Systems
Highly Cited
1990
Highly Cited
1990
Mapping rule-based systems into neural architecture
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