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HiGP: A high-performance Python package for Gaussian Processes

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Bibliographic Details
Published in:Journal of Open Source Software
Format: Online Article RSS Article
Published: 2026
Subjects:
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container_title Journal of Open Source Software
description
discipline_display Engineering & Technology
discipline_facet Engineering & Technology
format Online Article
RSS Article
genre Journal Article
id rss_article:7083
institution FRELIP
journal_source_facet Journal of Open Source Software
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle HiGP: A high-performance Python package for Gaussian Processes
Computer Science & Information Science
Computer Science & IT
Engineering & Technology
sub_discipline_display Computer Science & IT
sub_discipline_facet Computer Science & IT
subject_display Computer Science & Information Science
Computer Science & IT
Engineering & Technology
Computer Science & Information Science
Computer Science & IT
Engineering & Technology
subject_facet Computer Science & Information Science
Computer Science & IT
Engineering & Technology
title HiGP: A high-performance Python package for Gaussian Processes
title_auth HiGP: A high-performance Python package for Gaussian Processes
title_full HiGP: A high-performance Python package for Gaussian Processes
title_fullStr HiGP: A high-performance Python package for Gaussian Processes
title_full_unstemmed HiGP: A high-performance Python package for Gaussian Processes
title_short HiGP: A high-performance Python package for Gaussian Processes
title_sort higp: a high-performance python package for gaussian processes
topic Computer Science & Information Science
Computer Science & IT
Engineering & Technology
url https://joss.theoj.org/papers/10.21105/joss.08621