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74 lines (71 loc) · 2.41 KB
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# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: "pyAgrum/aGrUM"
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Pierre-Henri
family-names: WUILLEMIN
email: pierre-henri.wuillemin@lip6.fr
affiliation: Sorbonne Université / CNRS
orcid: 'https://orcid.org/0000-0003-3691-4886'
- given-names: Christophe
family-names: GONZALES
email: christophe.gonzales@lis-lab.fr
affiliation: AMU / CNRS
orcid: 'https://orcid.org/0009-0006-1633-5405'
identifiers:
- type: url
value: 'https://hal.archives-ouvertes.fr/hal-03135721'
description: >-
aGrUM/pyAgrum : a Toolbox to Build Models and
Algorithms for Probabilistic Graphical Models in
Python
- type: url
value: 'https://hal.archives-ouvertes.fr/hal-01509651'
description: 'aGrUM: a Graphical Universal Model framework'
repository-code: 'https://gitlab.com/agrumery/aGrUM'
url: 'https://agrum.gitlab.io/'
repository: 'https://github.com/agrumery/aGrUM'
abstract: >-
aGrUM is a C++ library for graphical models. It is
designed for easily building applications using graphical
models such as Bayesian networks, influence diagrams,
decision trees, GAI networks or Markov decision processes.
pyAgrum is a Python wrapper for the C++ aGrUM library
(using SWIG interface generator). It provides a high-level
interface to the part of aGrUM allowing to create, model,
learn, use, calculate with and embed Bayesian Networks and
other graphical models. Some specific (python and C++)
codes are added in order to simplify and extend the aGrUM
API.
keywords:
- Bayesian networks
- Probabilistic Graphical Models
- Causality
- Statistical learning
- Decision Making
- Artificial Intelligence
- Machine Learning
- C++
- Python
license:
- LGPL-3.0
- MIT
preferred-citation :
type: conference-paper
authors:
- given-names: Gaspard
family-names: Ducamp
- given-names: Christophe
family-names: Gonzales
- given-names: Pierre-Henri
family-names: Wuillemin
title: 'aGrUM/pyAgrum : a Toolbox to Build Models and Algorithms for Probabilistic Graphical Models in Python'
year: 2020
conference:
name: 10th International Conference on Probabilistic Graphical Models
url: https://hal.archives-ouvertes.fr/hal-03135721