Optimization Employing Gaussian Process-Based Surrogates

DOI10.1007/978-3-319-91143-4_26zbMath1397.62114OpenAlexW2860329578MaRDI QIDQ4689219

Udo von Toussaint, Roland Preuss

Publication date: 15 October 2018

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-91143-4_26

zbMATH Keywords

global optimizationGaussian processBayesian inferenceparametric studies

Mathematics Subject Classification ID

Gaussian processes (60G15) Bayesian inference (62F15)

Related Items (1)

Bayesian inference using Gaussian process surrogates in cancer modeling

Cites Work

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• Bayesian algorithms for one-dimensional global optimization
• Design and analysis of computer experiments. With comments and a rejoinder by the authors
• A taxonomy of global optimization methods based on response surfaces
• Bayesian Reasoning and Machine Learning

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