Computers and Internet Artificial Intelligence Belief Networks| 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. | |
| Belief Revision http://beliefrevision.org/ Software, publications, teaching material, and news on belief revision | |
| 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. | |
| B-Course - Dependence and classification modeling http://b-course.cs.helsinki.fi/ Dependence and classification modeling | |
| 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 | |
| Cause, chance and Bayesian statistics http://www.abelard.org/briefings/bayes.htm Briefing document with a short survey of Bayesian statistics | |
| 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 | |
| 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 | |
| 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. | |
| 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. | |
