|
PR: 8
| 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. - Read more http://www.pitt.edu |
|
PR: 7
| A Brief Introduction to Graphical Models and Bayesian Networks [No Description] - Read more http://www.cs.berkeley.edu |
|
PR: 7
| Bayesian Network Repository Maintained by Gal Elidan - over a dozen publicly available networks with documentation, in several popular interchange formats - Read more http://www.cs.huji.ac.il |
|
PR: 7
| 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 - Read more http://www.sis.pitt.edu |
|
PR: 7
| 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. - Read more http://www.cs.cmu.edu |
|
PR: 6
| 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. - Read more http://www.auai.org |
|
PR: 6
| Daphne's Approximate Group of Students (DAGS) Daphne Koller's research group on probabilistic representation, reasoning, and learning at Stanford University - Read more http://dags.stanford.edu |
|
PR: 5
| Belief Revision Software, publications, teaching material, and news on belief revision - from the Business and Technology Research Laboratory at the University of Newcastle, Australia - Read more http://beliefrevision.org |
|
PR: 4
| B-Course - Dependence and classification modeling A free, interactive tutorial on Bayesian modeling, in particular dependence and classification modeling. - Read more http://b-course.cs.helsinki.fi |
|
PR: 4
| 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. - Read more http://homepages.inf.ed.ac.uk |
|
PR: 4
| Cause, chance and Bayesian statistics Briefing document with a short survey of Bayesian statistics - Read more http://www.abelard.org |
|
PR: 2
| 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 - Read more http://www.niedermayer.ca |
Online Shopping Cart Development with PayPal Integration @ $600. Only
NEED A WEBSITE DESIGN?
5 pages website design with logo design and homepage flash intro @ $125. Only