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» Explaining inferences in Bayesian networks
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SBACPAD
2006
IEEE
148views Hardware» more  SBACPAD 2006»
15 years 5 months ago
Scalable Parallel Implementation of Bayesian Network to Junction Tree Conversion for Exact Inference
We present a scalable parallel implementation for converting a Bayesian network to a junction tree, which can then be used for a complete parallel implementation for exact inferen...
Vasanth Krishna Namasivayam, Animesh Pathak, Vikto...
BMCBI
2010
229views more  BMCBI 2010»
14 years 11 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck
AIED
2005
Springer
15 years 5 months ago
Inferring learning and attitudes from a Bayesian Network of log file data
A student's goals and attitudes while interacting with a tutor are typically unseen and unknowable. However their outward behavior (e.g. problem-solving time, mistakes and hel...
Ivon Arroyo, Beverly Park Woolf
IJAR
2000
140views more  IJAR 2000»
14 years 11 months ago
Belief updating in multiply sectioned Bayesian networks without repeated local propagations
Multiply sectioned Bayesian networks (MSBNs) provide a coherent and flexible formalism for representing uncertain knowledge in large domains. Global consistency among subnets in a...
Yang Xiang
AI
2010
Springer
14 years 11 months ago
Understanding the scalability of Bayesian network inference using clique tree growth curves
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...
Ole J. Mengshoel