Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic Expert Systems
Introduction to Bayesian Networks
Introduction to Bayesian Networks
Hybrid Propagation in Junction Trees
IPMU'94 Selected papers from the 5th International Conference on Processing and Management of Uncertainty in Knowledge-Based Systems, Advances in Intelligent Computing
A general algorithm for approximate inference and its application to hybrid bayes nets
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Inference in multiply sectioned Bayesian networks with extended Shafer-Shenoy and lazy propagation
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Lazy propagation in junction trees
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
HUGS: combining exact inference and Gibbs sampling in junction trees
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Optimization of inter-subnet belief updating in multiply sectioned Bayesian networks
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Iterative Multiagent Probabilistic Inference
IAT '06 Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology
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Multiply Sectioned Bayesian Networks(MSBNs) extend the junction tree based inference algorithms into a coherent framework for flexible modelling and effective inference in large domains. However, these junction tree based algorithms are limited by the need to maintain an exact representation of clique potentials. This paper presents a new unified inference framework for MSBNs that combines approximate inference algorithms and junction tree based inference algorithms, thereby circumvents this limitation. As a result our algorithm allow inference in much larger domains given the same computational resources. We believe it is the very first approximate inference algorithm for MSBNs.