Cautious Propagation in Bayesian Networks
Abstract
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′.
Cite
Text
Jensen. "Cautious Propagation in Bayesian Networks." Conference on Uncertainty in Artificial Intelligence, 1995.Markdown
[Jensen. "Cautious Propagation in Bayesian Networks." Conference on Uncertainty in Artificial Intelligence, 1995.](https://mlanthology.org/uai/1995/jensen1995uai-cautious/)BibTeX
@inproceedings{jensen1995uai-cautious,
title = {{Cautious Propagation in Bayesian Networks}},
author = {Jensen, Finn Verner},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {1995},
pages = {323-328},
url = {https://mlanthology.org/uai/1995/jensen1995uai-cautious/}
}