conference-paper
Open access
pgmpy: Probabilistic Graphical Models using Python
Research footprint
At a glance
- Citations
- 233
- References
- 1
- Comments
- 0
Paper overview
Abstract
Probabilistic Graphical Models (PGM) is a technique of compactly representing a joint distribution by exploiting dependencies between the random variables. It also allows us to do inference on joint distributions in a computationally cheaper way than the traditional methods. PGMs are widely used in the field of speech recognition, information extraction, image segmentation, modelling gene regulatory networks.
Record transparency
Publication details
- DOI
- 10.25080/majora-7b98e3ed-001
- OpenAlex
- W2275580678
- Document type
- conference-paper
- Language
- EN
- Source
- Proceedings of the Python in Science Conferences
- Last metadata update
Comments
Log in to join the discussion.