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

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

Kevin Murphy's tutorial, including a recommended reading list.

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

Research group at the University of Pittsburgh with links to books and software on probabilistic, decision-theoretic, and econometric graphical models

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

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

Briefing document with a short survey of Bayesian statistics

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

A survey and tutorial by Daryle Niedermayer - covers material on Bayesian inference in general and selected industrial applications of graphical models