Bayesian Inference in the Presence of Determinism
Abstract
In this paper, we consider the problem of performing inference on Bayesian networks which exhibit a substantial degree of determinism. We improve upon the determinismexploiting inference algorithm presented in [4], showing that the information brought to light by constraint propagation may be exploited to a much greater extent than has been previously possible. This is confirmed with theoretical and empirical studies.
Cite
Text
Larkin and Dechter. "Bayesian Inference in the Presence of Determinism." Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003.Markdown
[Larkin and Dechter. "Bayesian Inference in the Presence of Determinism." Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003.](https://mlanthology.org/aistats/2003/larkin2003aistats-bayesian/)BibTeX
@inproceedings{larkin2003aistats-bayesian,
title = {{Bayesian Inference in the Presence of Determinism}},
author = {Larkin, David and Dechter, Rina},
booktitle = {Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics},
year = {2003},
pages = {187-194},
volume = {R4},
url = {https://mlanthology.org/aistats/2003/larkin2003aistats-bayesian/}
}