Published October 25, 2021
| Version nips21
Software
Open
aditya95sriram/bn-slim: NeurIPS 2021
Description
Version submitted to NeurIPS 2021 as a part of the paper titled Learning Fast-Inference Bayesian Networks. Implements bounded state space size Bayesian Network learning.
Notes
Files
aditya95sriram/bn-slim-nips21.zip
Files
(7.7 MB)
Name | Size | Download all |
---|---|---|
md5:53a9ecab9cfe985caa346124c6a03798
|
7.7 MB | Preview Download |
Additional details
Related works
- Is supplement to
- https://github.com/aditya95sriram/bn-slim/tree/nips21 (URL)
Funding
- FWF Austrian Science Fund
- SAT-Based Local Improvement Methods (SLIM) P 32441
- FWF Austrian Science Fund
- Vollantrag zu Logical Methods in Computer Science W 1255
References
- Benjumeda, Marco and Bielza, Concha and Larrañaga Pedro. Learning tractable Bayesian Networks in the space of elimination orders. Artificial Intelligence, 274:66–90, 2019
- Scanagatta, Mauro. BLIP – Bayesian network learning and inference package, 2015. URL: https: //ipg.idsia.ch/software/blip