Gourt > Computers > Artificial Intelligence > Belief Networks (4)
A Bayesian network or Bayesian belief network or just belief network is a form of probabilistic graphical model. Bayesian network represents joint probability distribution of a set of variables with explicit independency assumptions.
Definition
A Bayesian network is a directed acyclic graph of nodes representing variables and arcs representing dependence relations among the variables. If there is an arc from node A to another node B, then values of variable B depend directly on values of A and A is called a parent of B. If a node has a known value, it is said to be an evidence node. A node can represent any kind of variable, be it an observed measurement, a parameter, a latent variable, or a hypothesis. Nodes are not restricted to representing random variables; this is what is "Bayesian" about a Bayesian network. Let the variables be X(1), ..., X(n). Let parents(A) be the parents of the node A. Then the joint distribution for X(1) through X(n) is represented as the product of the probability distributions for i = 1 to n. If X has no parents, its probability distribution is said to be unconditional, otherwise it is conditional.
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Neural Networks :: Artificial Intelligence
Probability :: Math
Bayesian Analysis :: Statistics
Barracuda Networks Detects and Blocks "Backdoor" Virus Sent via ... - MarketWatch
Fri, 10 Oct 2008 01:45:40 -0000
Barracuda Networks Detects and Blocks "Backdoor" Virus Sent via ...MarketWatch - 16 hours agoBarracuda Networks was one of the first vendors to profile the malware and quickly categorized it in the Barracuda Real-Time Protection system to block the ...
Untangle turns ordinary PC into security box - InfoWorld
Tue, 16 Sep 2008 14:11:36 -0000
Untangle turns ordinary PC into security boxInfoWorld, CA - Sep 16, 2008The anti-spam element is a mixture of Bayesian filtering, real-time block lists, and the open-source Razor. Untangle even claims that the PC used to run all ...
Integrative bioinformatics analysis of transcriptional regulatory ... - 7thSpace Interactive (press release)
Mon, 29 Sep 2008 11:52:09 -0000
Integrative bioinformatics analysis of transcriptional regulatory ...7thSpace Interactive (press release), NY - Sep 29, 2008... of breast cancer into a Bayesian Network, and searched for cis-regulatory motifs statistically associated with given histological grades and prognosis. ...
Autogenomics, Hisamitsu Pharmaceutical, Chiba Prefecture ... - bioArray News (subscription)
Tue, 30 Sep 2008 19:05:50 -0000
Autogenomics, Hisamitsu Pharmaceutical, Chiba Prefecture ...bioArray News (subscription), NY - Sep 30, 2008Other described methods include modifications of Bayesian inferential methods and application of those methods to determining cause and effect relationships ...
Outstanding spam capture rate and low false positives with GFI ... - ITworld.com
Fri, 03 Oct 2008 13:23:50 -0000
Outstanding spam capture rate and low false positives with GFI ...ITworld.com, MA - Oct 3, 2008With SpamRazer filtering, IP reputation filtering, Bayesian and other advanced anti-spam technology modules, an ultra high capture rate is obtained as well ...
LatentView adjudged as one of the winners at the INFORMS Data ... - PR-Inside.com (Pressemitteilung)
Fri, 26 Sep 2008 18:38:11 -0000
LatentView adjudged as one of the winners at the INFORMS Data ...PR-Inside.com (Pressemitteilung), Austria - Sep 26, 2008Optimization algorithms, Bayesian networks, CART, etc were explored over and above the usual predictive modeling techniques. Overall, this contest was an ...
A Brief Introduction to Graphical Models and Bayesian Networks - Kevin Murphy's tutorial, including a recommended reading list.
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
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.
Meta Description: [ Web site for the Association for Uncertainty in Artificial Intelligence ]
Bayesian Network Repository - Maintained by Gal Elidan - over a dozen publicly available networks with documentation, in several popular interchange formats
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.
Meta 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 param... ]
Cause, chance and Bayesian statistics - Briefing document with a short survey of Bayesian statistics
Meta Description: [ briefing document to facilitate understanding Bayesian statistics. The statistical theory developed by Thomas Bayes enables analysis of conditional and marginal probabilities. Bayesian statistics enables logical inference ]
Daphne's Approximate Group of Students (DAGS) - Daphne Koller's research group on probabilistic representation, reasoning, and learning at Stanford University
Meta Description: [ DAGS - Daphne Koller's Research Group working on Probabilistic Reasoning with Bayesian Networks, Markov Decision Processes and Probabilistic Relational Models. ]
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
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
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
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.
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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.
Meta Description: [ Query DAGs: A Practical Paradigm for Implementing Belief-Network Inference ]
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Conversation Scene Analysis: Conversation Scene Analysis with Dynamic Bayesian Network based on Visual Head Tracking IEEE ICME'06, July, 2006 |
