On Bayesian Network Inference with Simple Propagation
Abstract
\emphSimple Propagation (SP) was recently proposed as a new join tree propagation algorithm for exact inference in discrete Bayesian networks and empirically shown to be faster than \emphLazy Propagation (LP) when applied on optimal (or close to) join trees built from real-world and benchmark Bayesian networks. This paper extends SP in two directions. First, we propose and empirically evaluate eight heuristics for determining elimination orderings in SP. Second, we show that the relevant potentials in SP are precisely those in LP.
Cite
Text
Butz et al. "On Bayesian Network Inference with Simple Propagation." Proceedings of the Eighth International Conference on Probabilistic Graphical Models, 2016.Markdown
[Butz et al. "On Bayesian Network Inference with Simple Propagation." Proceedings of the Eighth International Conference on Probabilistic Graphical Models, 2016.](https://mlanthology.org/pgm/2016/butz2016pgm-bayesian/)BibTeX
@inproceedings{butz2016pgm-bayesian,
title = {{On Bayesian Network Inference with Simple Propagation}},
author = {Butz, Cory J. and Oliveira, Jhonatan S. and dos Santos, André E. and Madsen, Anders L.},
booktitle = {Proceedings of the Eighth International Conference on Probabilistic Graphical Models},
year = {2016},
pages = {62-73},
volume = {52},
url = {https://mlanthology.org/pgm/2016/butz2016pgm-bayesian/}
}