Contents  > Computers  > Artificial Intelligence  > Belief Networks

See also:

• Computers: Artificial Intelligence: Neural Networks  (262)
• Science: Math: Probability  (98)
• Science: Math: Statistics: Bayesian Analysis  (20)

• A Brief Introduction to Graphical Models and Bayesian Networks - Kevin Murphy's tutorial, including a recommended reading list.

  Association 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. http://www.auai.org/

  Bayesian Network Repository Maintained by Gal Elidan - over a dozen publicly available networks with documentation, in several popular interchange formats http://www.cs.huji.ac.il/labs/compbio/Repository/

  B-Course - Dependence and classification modeling A free, interactive tutorial on Bayesian modeling, in particular dependence and classification modeling. http://b-course.cs.helsinki.fi

  Belief 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. http://homepages.inf.ed.ac.uk/amos/belief.html

  Belief Revision Software, publications, teaching material, and news on belief revision - from the Business and Technology Research Laboratory at the University of Newcastle, Australia http://beliefrevision.org

  Cause, chance and Bayesian statistics Briefing document with a short survey of Bayesian statistics http://www.abelard.org/briefings/bayes.htm

  Daphne's Approximate Group of Students (DAGS) Daphne Koller's research group on probabilistic representation, reasoning, and learning at Stanford University http://dags.stanford.edu

  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 http://www.sis.pitt.edu/~dsl/

  An 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 http://www.niedermayer.ca/papers/bayesian/

  Learning 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 http://www.cs.huji.ac.il/~nirf/Nips01-Tutorial/

  Qualitative 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. http://www.pitt.edu/~druzdzel/abstracts/aisb.html

  Query 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. http://www.cs.cmu.edu/afs/cs/project/jair/pub/volume6/darwiche97a-html/jair-f.html