Conferences and Events 3
Projects and Systems 7
Software 30
| | Neural Networks - Artificial Intelligence, Computers 268
Probability - Math, Science 102
Bayesian Analysis - Statistics, Math, Science 21
 A Brief Introduction to Graphical Models and Bayesian NetworksA Brief Introduction to Graphical Models and Bayesian Networks
 
Kevin Murphy's tutorial, including a recommended reading list.
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Association for Uncertainty in Artificial IntelligenceAssociation for Uncertainty in Artificial Intelligence
 Main association for belief network researchers. Runs the annual Uncertainty in Artificial Intelligence (UAI) conferences, and the UAI mailing list.
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Bayesian Network RepositoryBayesian Network Repository
 Maintained by Gal Elidan - over a dozen publicly available networks with documentation, in several popular interchange formats
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B-Course - Dependence and classification modelingB-Course - Dependence and classification modeling
 A free, interactive tutorial on Bayesian modeling, in particular dependence and classification modeling.
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Belief Networks and Variational Methods : Amos StorkeyBelief Networks and Variational Methods : Amos Storkey
 Dynamic Trees are mixtures of tree structured belief networks, and are used as models for image segmentation and tracking.
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Belief RevisionBelief Revision
 Software, publications, teaching material, and news on belief revision - from the Business and Technology Research Laboratory at the University of Newcastle, Australia
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Cause, chance and Bayesian statisticsCause, chance and Bayesian statistics
 Briefing document with a short survey of Bayesian statistics
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Daphne's Approximate Group of Students (DAGS)Daphne's Approximate Group of Students (DAGS)
 Daphne Koller's research group on probabilistic representation, reasoning, and learning at Stanford University
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Decision Systems Lab (DSL)Decision Systems Lab (DSL)
 Research group at the University of Pittsburgh with links to books and software on probabilistic, decision-theoretic, and econometric graphical models
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An Introduction to Bayesian Networks and Their Contemporary ApplicationsAn Introduction to Bayesian Networks and Their Contemporary Applications
 A survey and tutorial by Daryle Niedermayer - covers material on Bayesian inference in general and selected industrial applications of graphical models
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Learning Bayesian Networks from DataLearning Bayesian Networks from Data
 Slides and additional notes from a tutorial by Nir Friedman and Daphne Koller on automated learning of belief networks, given at the Neural Information Processing Systems (NIPS-2001) conference
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Qualitative Verbal Explanations in Bayesian Belief NetworksQualitative Verbal Explanations in Bayesian Belief Networks
 Paper about combining probabilistic models and human-intuitive approaches to modeling uncertainty by generating qualitative verbal explanations of reasoning.
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Query DAGs: A Practical Paradigm for Implementing Belief-Network InferenceQuery DAGs: A Practical Paradigm for Implementing Belief-Network Inference
 Article published in JAIR (Journal of AI Research) about a way to implement belief networks by compiling networks into arithmetic expressions and then answering queries using an evaluation algorithm.
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