Primula-3for Probabilistic Modeling and Reasoning on Graph Data
Abstract
The Primula system is a versatile software tool for modeling and reasoning with probabilistic relational structures based on the symbolic Relational Bayesian Networks (RBN) language. The new version 3 of Primula extends previous versions by adding support for categorical variables, and by integrating Graph Neural Networks (GNN) as model components into a full generative RBN model, thus combining the predictive power and scalable learning tools of GNNs with the high expressivity and flexible inference capabilities of RBNs.
Cite
Text
Pojer and Jaeger. "Primula-3for Probabilistic Modeling and Reasoning on Graph Data." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2025. doi:10.1007/978-3-032-06129-4_35Markdown
[Pojer and Jaeger. "Primula-3for Probabilistic Modeling and Reasoning on Graph Data." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2025.](https://mlanthology.org/ecmlpkdd/2025/pojer2025ecmlpkdd-primula3for/) doi:10.1007/978-3-032-06129-4_35BibTeX
@inproceedings{pojer2025ecmlpkdd-primula3for,
title = {{Primula-3for Probabilistic Modeling and Reasoning on Graph Data}},
author = {Pojer, Raffaele and Jaeger, Manfred},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2025},
pages = {481-485},
doi = {10.1007/978-3-032-06129-4_35},
url = {https://mlanthology.org/ecmlpkdd/2025/pojer2025ecmlpkdd-primula3for/}
}