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| Main Author: | |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.19158 |
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| _version_ | 1866910624149143552 |
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| author | Leonelli, Manuele |
| author_facet | Leonelli, Manuele |
| contents | Bayesian networks (BNs) are widely used for modeling complex systems with uncertainty, yet repositories of pre-built BNs remain limited. This paper introduces bnRep, an open-source R package offering a comprehensive collection of documented BNs, facilitating benchmarking, replicability, and education. With over 200 networks from academic publications, bnRep integrates seamlessly with bnlearn and other R packages, providing users with interactive tools for network exploration. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_19158 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | bnRep: A repository of Bayesian networks from the academic literature Leonelli, Manuele Artificial Intelligence Physics and Society Bayesian networks (BNs) are widely used for modeling complex systems with uncertainty, yet repositories of pre-built BNs remain limited. This paper introduces bnRep, an open-source R package offering a comprehensive collection of documented BNs, facilitating benchmarking, replicability, and education. With over 200 networks from academic publications, bnRep integrates seamlessly with bnlearn and other R packages, providing users with interactive tools for network exploration. |
| title | bnRep: A repository of Bayesian networks from the academic literature |
| topic | Artificial Intelligence Physics and Society |
| url | https://arxiv.org/abs/2409.19158 |