Explanation in Bayesian belief networks
Explanation in Bayesian belief networks
Analysis in HUGIN of data conflict
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
Sensitivity Analysis in Bayesian Networks
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
A service provisioning system for distributed personalization with private data protection
Journal of Systems and Software
Lazy propagation in junction trees
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
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Consider the situation where some evidence e has been entered to a Bayesian network. When performing conflict analysis, sensitivity analysis, or when answering questions like "What if the finding on X had been y instead of x?", you need probabilities P(e′|h) where e′ is a subset of e, and h is a configuration of a (possibly empty) set of variables. Cautious propagation is a modification of HUGIN propagation into a Shafer-Shenoy-like architecture. It is less efficient than HUGIN propagation; however, it provides easy access to P(e′|h) for a great deal of relevant subsets e′.