Wectar - Computers - Artificial Intelligence - Belief Networks

Subcategories
Conferences and Events	Projects and Systems	Software

	Uncertainty in Artificial Intelligence (UAI) URL: http://www.auai.org/ ODP description: Main conference for Belief Networks. Page title: Assoc for Uncertainty in AI Page description: Web site for the Association for Uncertainty in Artificial Intelligence
	LAPLACE Group - Bayesian Models for Perception, Inference and Action URL: http://www-laplace.imag.fr ODP description: Probabilistic reasoning and genetic algorithms for perception, inference and action: Bayesian cognitive and brain models, software for robotics, probabilistic inference engine Page title: Bayesian programming Bayesian networks cognitive robotics
	Belief Revision URL: http://beliefrevision.org ODP description: Software, publications, teaching material, and news on belief revision - from the Business and Technology Research Laboratory at the University of Newcastle, Australia Page title: Welcome to Belief Revision!
	Belief Networks and Variational Methods : Amos Storkey URL: http://www.anc.ed.ac.uk/~amos/belief.html ODP description: Dynamic Trees are mixtures of tree structured belief networks, and are used as models for image segmentation and tracking. Page title: Amos Storkey - Research - Belief Networks Page description: Tutorial: Introduction to Belief Networks. A simple illustrated tutorial on belief networks (or Bayesian networks), with links and references for further reading. This tutorial focusses on the introductory issues of design of Bayes nets, inference in belief nets, and learning belief network parameters.
	An Introduction to Bayesian Networks and Their Contemporary Applications URL: http://www.niedermayer.ca/papers/bayesian/ ODP description: A survey and tutorial by Daryle Niedermayer - covers material on Bayesian inference in general and selected industrial applications of graphical models Page title: An Introduction to Bayesian Networks and their Contemporary Applications
	Cause, chance and Bayesian statistics URL: http://www.abelard.org/briefings/bayes.htm ODP description: Briefing document to facilitate understanding Bayesian statistics, including its application to intelligence quotient statistics. Page title: cause, chance and Bayesian statistics - Bayes theory for conditional and marginal probabilities
	Qualitative Verbal Explanations in Bayesian Belief Networks URL: http://www.pitt.edu/~druzdzel/abstracts/aisb.html ODP description: Paper about combining probabilistic models and human-intuitive approaches to modeling uncertainty by generating qualitative verbal explanations of reasoning.
	Daphne's Approximate Group of Students (DAGS) URL: http://dags.stanford.edu ODP description: Daphne Koller's research group on probabilistic representation, reasoning, and learning at Stanford University Page title: DAGS - Daphne Koller's Research Group Page description: DAGS - Daphne Koller's Research Group working on Probabilistic Reasoning with Bayesian Networks, Markov Decision Processes and Probabilistic Relational Models.
	A Brief Introduction to Graphical Models and Bayesian Networks URL: http://www.cs.berkeley.edu/~murphyk/Bayes/bayes.html ODP description: Kevin Murphy's tutorial, including a recommended reading list. Page title: Graphical Models
	Decision Systems Lab (DSL) URL: http://www.sis.pitt.edu/~dsl/ ODP description: Research group at the University of Pittsburgh with links to books and software on probabilistic, decision-theoretic, and econometric graphical models Page title: GeNIe & SMILE
	Query DAGs: A Practical Paradigm for Implementing Belief-Network Inference URL: http://www.cs.cmu.edu/afs/cs/project/jair/pub/volume6/darwiche97a-html/jair-f.html ODP description: 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. Page description: Query DAGs: A Practical Paradigm for Implementing Belief-Network Inference
	Learning Bayesian Networks from Data URL: http://www.cs.huji.ac.il/~nirf/Nips01-Tutorial/ ODP description: 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 Page title: NIPS 2001 Tutorial: Learning Bayesian Networks From Data
	B-Course - Dependence and classification modeling URL: http://b-course.cs.helsinki.fi ODP description: A free, interactive tutorial on Bayesian modeling, in particular dependence and classification modeling.
	Bayesian Network Repository URL: http://www.cs.huji.ac.il/labs/compbio/Repository/ ODP description: Maintained by Gal Elidan - over a dozen publicly available networks with documentation, in several popular interchange formats