kooplearn: A scikit-learn compatible library of algorithms for evolution operator learning
kooplearn: A scikit-learn compatible library of algorithms for evolution operator learning - Published in JOSS (2026)
https://github.com/machine-learning-dynamical-systems/kooplearn
Science Score: 87.0%
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Published in Journal of Open Source Software
Last synced: 13 days ago
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JOSS Publication
kooplearn: A scikit-learn compatible library of algorithms for evolution operator learning
Published
June 25, 2026
Volume 11, Issue 122, Page 10342
Authors
Giacomo Turri
Computational Statistics and Machine Learning, Italian Institute of Technology, Genoa, Italy
Computational Statistics and Machine Learning, Italian Institute of Technology, Genoa, Italy
Grégoire Pacreau
Centre de Mathématiques Appliquées, École Polytechnique, Palaiseau, France
Centre de Mathématiques Appliquées, École Polytechnique, Palaiseau, France
Timothée Devergne
Atomistic Simulations, Italian Institute of Technology, Genoa, Italy, Computational Statistics and Machine Learning, Italian Institute of Technology, Genoa, Italy
Atomistic Simulations, Italian Institute of Technology, Genoa, Italy, Computational Statistics and Machine Learning, Italian Institute of Technology, Genoa, Italy
Daniel Ordoñez-Apraez
Computational Statistics and Machine Learning, Italian Institute of Technology, Genoa, Italy
Computational Statistics and Machine Learning, Italian Institute of Technology, Genoa, Italy
Erfan Mirzaei
Computational Statistics and Machine Learning, Italian Institute of Technology, Genoa, Italy
Computational Statistics and Machine Learning, Italian Institute of Technology, Genoa, Italy
Bruno Belucci
Paris Dauphine University, Paris, France
Paris Dauphine University, Paris, France
Vladimir R. Kostic
Computational Statistics and Machine Learning, Italian Institute of Technology, Genoa, Italy, Department of Mathematics and Informatics, Faculty of Science, University of Novi Sad, Novi Sad, Serbia
Computational Statistics and Machine Learning, Italian Institute of Technology, Genoa, Italy, Department of Mathematics and Informatics, Faculty of Science, University of Novi Sad, Novi Sad, Serbia
Tags
dynamical systems evolution operator koopman operator transfer operator operator learning machine learning representation learningIssues and Pull Requests
Last synced: 3 months ago
All Time
- Total issues: 5
- Total pull requests: 20
- Average time to close issues: over 1 year
- Average time to close pull requests: 7 days
- Total issue authors: 3
- Total pull request authors: 6
- Average comments per issue: 1.6
- Average comments per pull request: 0.45
- Merged pull requests: 14
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 4
- Average time to close issues: N/A
- Average time to close pull requests: 10 days
- Issue authors: 0
- Pull request authors: 2
- Average comments per issue: 0
- Average comments per pull request: 0.5
- Merged pull requests: 4
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- pietronvll (2)
- Danfoa (2)
- Giodiro (1)
Pull Request Authors
- pietronvll (7)
- Danfoa (4)
- g-turri (4)
- Giodiro (2)
- mitchellostrow (2)
- DevergneTimothee (1)
Top Labels
Issue Labels
enhancement (1)
documentation (1)
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- pypi 304 last-month
- Total dependent packages: 0
- Total dependent repositories: 2
- Total versions: 54
- Total maintainers: 1
pypi.org: kooplearn
A python package for evolution operator learning
- Documentation: https://kooplearn.readthedocs.io/
- License: mit
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Latest release: 2.0.3
published about 2 months ago
Rankings
Dependent packages count: 10.1%
Dependent repos count: 11.5%
Stargazers count: 15.2%
Average: 15.6%
Forks count: 19.1%
Downloads: 21.7%
Maintainers (1)
Last synced:
28 days ago