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«Top»  : «Computers»  : «Artificial Intelligence»  : Belief Networks Sites

A Brief Introduction to Graphical Models and Bayesian Networks
Kevin murphy's tutorial , including a recommended reading list.
www.cs.berkeley.edu/~murphyk/Bayes/bayes.html
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 models
www.niedermayer.ca/papers/bayesian
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.
www.auai.org
B-Course - Dependence and classification modeling
A free , interactive tutorial on bayesian modeling , in particular dependence and classification modeling.
b-course.cs.helsinki.fi
Bayesian Network Repository
Maintained by gal elidan - over a dozen publicly available networks with documentation , in several popular interchange formats
www.cs.huji.ac.il/labs/compbio/Repository
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.
www.anc.ed.ac.uk/~amos/belief.html
Belief Revision
Software , publications , teaching material , and news on belief revision - from the business and technology research laboratory at the university of newcastle , australia
beliefrevision.org
Cause, chance and Bayesian statistics
Briefing document with a short survey of bayesian statistics
www.abelard.org/briefings/bayes.htm
Daphne's Approximate Group of Students (DAGS)
Daphne koller's research group on probabilistic representation , reasoning , and learning at stanford university
dags.stanford.edu
Decision Systems Lab (DSL)
Research group at the university of pittsburgh with links to books and software on probabilistic , decision-theoretic , and econometric graphical models
www.sis.pitt.edu/~dsl
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 engine
www-laplace.imag.fr
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
www.cs.huji.ac.il/~nirf/Nips01-Tutorial
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.
www.pitt.edu/~druzdzel/abstracts/aisb.html
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.
www.cs.cmu.edu/afs/cs/project/jair/pub/volume6/darwiche97a-html/jair-f.html

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