Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Management Science
A sufficiently fast algorithm for finding close to optimal clique trees
Artificial Intelligence
Probabilistic Networks and Expert Systems
Probabilistic Networks and Expert Systems
Decomposing Bayesian networks: triangulation of the moral graph with genetic algorithms
Statistics and Computing
Stable local computation with conditional Gaussian distributions
Statistics and Computing
Directed reduction algorithms and decomposable graphs
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
Lazy propagation in junction trees
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Maximal prime subgraph decomposition of Bayesian networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Belief update in CLG Bayesian networks with lazy propagation
International Journal of Approximate Reasoning
Improvements to message computation in lazy propagation
International Journal of Approximate Reasoning
Good practice in Bayesian network modelling
Environmental Modelling & Software
Model-based clustering of high-dimensional data: Variable selection versus facet determination
International Journal of Approximate Reasoning
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This paper describes a scheme for local computation in conditional Gaussian Bayesian networks that combines the approach of Lauritzen and Jensen (2001) with some elements of Shachter and Kenley (1989). Message passing takes place on an elimination tree structure rather than the more compact (and usual) junction tree of cliques. This yields a local computation scheme in which all calculations involving the continuous variables are performed by manipulating univariate regressions, and hence matrix operations are avoided.