See also:

• Computers: Artificial Intelligence: Neural Networks  (290)
• Science: Math: Probability  (111)
• Science: Math: Statistics: Bayesian Analysis  (22)

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.

Bayesian Network Repository - - Maintained by Gal Elidan - over a dozen publicly available networks with documentation, in several popular interchange format.

B-Course - Dependence and classification modeling - - A free, interactive tutorial on Bayesian modeling, in particular dependence and classification modeling.

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.

Belief Revision - - Software, publications, teaching material, and news on belief revision - from the Business and Technology Research Laboratory at the University of Newcastle, Australi.

Cause, chance and Bayesian statistics - - Briefing document with a short survey of Bayesian statistic.

Daphne's Approximate Group of Students (DAGS) - - Daphne Koller's research group on probabilistic representation, reasoning, and learning at Stanford Universit.

Decision Systems Lab (DSL) - - Research group at the University of Pittsburgh with links to books and software on probabilistic, decision-theoretic, and econometric graphical model.

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 model.

LAPLACE Group - Bayesian Models for Perception, Inference and Action - - Probabilistic reasoning and genetic algorithms for perception, inference and action: Bayesian cognitive and brain models, software for robotics, probabilistic inference engin.

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) conferenc.

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.

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.