SMT 2.0: A Surrogate Modeling Toolbox with a focus on hierarchical and mixed variables Gaussian processes

The Surrogate Modeling Toolbox (SMT) is an open-source Python package that offers a collection of surrogate modeling methods, sampling techniques, and a set of sample problems. This paper presents SMT 2.0, a major new release of SMT that introduces significant upgrades and new features to the toolbo...

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Bibliographic Details

Published in:	Advances in engineering software (1992) Vol. 188; no. 103571; p. 103571
Main Authors:	Saves, Paul, Lafage, Rémi, Bartoli, Nathalie, Diouane, Youssef, Bussemaker, Jasper, Lefebvre, Thierry, Hwang, John T., Morlier, Joseph, Martins, Joaquim R.R.A.
Format:	Journal Article
Language:	English
Published:	Elsevier 01.02.2024
Subjects:	Computer Science Modeling and Simulation Gaussian process Hierarchical problems Hierarchical and mixed-categorical inputs I-GAIA Surrogate modeling Meta variables Kriging
ISSN:	0965-9978
Online Access:	Get full text
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