Continuous Time Bayesian Network Reasoning and Learning Engine
Abstract
We present a continuous time Bayesian network reasoning and learning engine (CTBN-RLE). A continuous time Bayesian network (CTBN) provides a compact (factored) description of a continuous-time Markov process. This software provides libraries and programs for most of the algorithms developed for CTBNs. For learning, CTBN-RLE implements structure and parameter learning for both complete and partial data. For inference, it implements exact inference and Gibbs and importance sampling approximate inference for any type of evidence pattern. Additionally, the library supplies visualization methods for graphically displaying CTBNs or trajectories of evidence.
Cite
Text
Shelton et al. "Continuous Time Bayesian Network Reasoning and Learning Engine." Machine Learning Open Source Software, 2010.Markdown
[Shelton et al. "Continuous Time Bayesian Network Reasoning and Learning Engine." Machine Learning Open Source Software, 2010.](https://mlanthology.org/mloss/2010/shelton2010jmlr-continuous/)BibTeX
@article{shelton2010jmlr-continuous,
title = {{Continuous Time Bayesian Network Reasoning and Learning Engine}},
author = {Shelton, Christian R. and Fan, Yu and Lam, William and Lee, Joon and Xu, Jing},
journal = {Machine Learning Open Source Software},
year = {2010},
pages = {1137-1140},
volume = {11},
url = {https://mlanthology.org/mloss/2010/shelton2010jmlr-continuous/}
}