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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. (infos)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. (infos)
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. (infos)
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. (infos)
A Brief Introduction to Graphical Models and Bayesian Networks
Kevin Murphy's tutorial, including a recommended reading list. (infos)
B-Course - Dependence and classification modeling
A free, interactive tutorial on Bayesian modeling, in particular dependence and classification modeling. (infos)
Cause, chance and Bayesian statistics
Briefing document with a short survey of Bayesian statistics (infos)
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 (infos)
Belief Revision
Software, publications, teaching material, and news on belief revision - from the Business and Technology Research Laboratory at the University of Newcastle, Australia (infos)
Daphne's Approximate Group of Students (DAGS)
Daphne Koller's research group on probabilistic representation, reasoning, and learning at Stanford University (infos)