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pyGPGO: Bayesian Optimization for Python

pyGPGO: Bayesian Optimization for Python - Published in JOSS (2017)

https://github.com/hawk31/pygpgo

Science Score: 87.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
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    codemeta.json file
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    .zenodo.json file
  • ✓
    DOI references
    Found 1 DOI reference(s) in JOSS metadata
  • ○
    Academic links in README
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    Academic email domains
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    Institutional organization owner
  • ✓
    JOSS paper metadata
    Published in Journal of Open Source Software
Last synced: 9 months ago · JSON representation

JOSS Publication

pyGPGO: Bayesian Optimization for Python
Published
November 02, 2017
DOI
Volume 2, Issue 19, Page 431
Authors
José Jiménez ORCID
Computational Biophysics Laboratory, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Carrer del Dr. Aiguader 88. Barcelona 08003, Spain.
Josep Ginebra ORCID
Department of Statistics and Operations Research. Universitat Politècnica de Catalunya (UPC). Av. Diagonal 647, Barcelona 08028, Spain.
Editor
Arfon Smith ORCID
Tags
machine-learning bayesian optimization
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Packages

  • Total packages: 1
  • Total downloads:
    • pypi 966 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 5
  • Total maintainers: 1
pypi.org: pygpgo

Bayesian Optimization tools in Python

  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 966 Last month
Rankings
Downloads: 4.1%
Stargazers count: 4.4%
Forks count: 5.5%
Average: 9.1%
Dependent packages count: 10.0%
Dependent repos count: 21.7%
Maintainers (1)
Jose.Jimenez
Last synced: 9 months ago