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Query DAGs: A Practical Paradigm for Implementing Belief-Network Inference

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

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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Qualitative Verbal Explanations in Bayesian Belief Networks

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

Paper about combining probabilistic models and human-intuitive approaches to modeling uncertainty by generating qualitative verbal explanations of reasoning.

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Learning Bayesian Networks from Data

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

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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Decision Systems Lab (DSL)

http://www.sis.pitt.edu/~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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Daphne's Approximate Group of Students (DAGS)

http://dags.stanford.edu/

Daphne Koller's research group on probabilistic representation, reasoning, and learning at Stanford University

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Belief Revision

http://beliefrevision.org/

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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Belief Networks and Variational Methods : Amos Storkey

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

Dynamic Trees are mixtures of tree structured belief networks, and are used as models for image segmentation and tracking.

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B-Course - Dependence and classification modeling

http://b-course.cs.helsinki.fi/

A free, interactive tutorial on Bayesian modeling, in particular dependence and classification modeling.

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Association for Uncertainty in Artificial Intelligence

http://www.auai.org/

Main association for belief network researchers. Runs the annual Uncertainty in Artificial Intelligence (UAI) conferences, and the UAI mailing list.

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