PyBADS: Fast and robust black-box optimization in Python

dc.contributor.affiliationUniversity of Geneva-Singh, Gurjeet Sangra
dc.contributor.authorSingh, Gurjeet Sangra
dc.date.accessioned2025-04-29T14:02:36Z
dc.date.issued2024-02-23
dc.date.issued2024-02-23
dc.descriptionThis upload archives the v1.0.4 release of PyBADS, as prepared for submission to the Jounral of Open Source Software (JOSS). PyBADS  is a Python implementation of the Bayesian Adaptive Direct Search (BADS) algorithm for solving difficult and mildly expensive optimization problems. BADS has been intensively tested for fitting a variety of computational models, and is currently being used in many computational labs around the world.
dc.identifierhttps://doi.org/10.5281/zenodo.10696782
dc.identifier.urihttps://datakatalogi.helsinki.fi/handle/123456789/5229
dc.rights.licensebsd-3-clause
dc.subjectBayesian optimization
dc.subjectmachine learning
dc.subjectblack-box optimization
dc.subjectcomputational statistics
dc.subjectprobabilistic modeling
dc.subjectgaussian processes
dc.titlePyBADS: Fast and robust black-box optimization in Python
dc.typesoftware
Zenodo


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