Summary of Bnrep: a Repository Of Bayesian Networks From the Academic Literature, by Manuele Leonelli
bnRep: A repository of Bayesian networks from the academic literature
by Manuele Leonelli
First submitted to arxiv on: 27 Sep 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Physics and Society (physics.soc-ph)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel open-source R package called bnRep is introduced in this paper, which offers a comprehensive collection of Bayesian networks (BNs) from over 200 academic publications. The package enables benchmarking, replicability, and education by facilitating the integration of BNs with other R packages such as bnlearn. This development aims to bridge the gap between the widespread use of BNs for modeling complex systems with uncertainty and the limited availability of pre-built BN repositories. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper provides a set of Bayesian networks that can be used to model complex systems with uncertainty. It offers over 200 networks from academic publications, which can be easily integrated into other R packages like bnlearn. This is useful for people who want to use Bayesian networks but don’t have the time or expertise to build their own. |
