Gaussian processes for computer experiments

François Bachoc (), Emile Contal, Hassan Maatouk () and Didier Rulliere ()
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François Bachoc: LPMA - Laboratoire de Probabilités et Modèles Aléatoires - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique
Emile Contal: CMLA - Centre de Mathématiques et de Leurs Applications - ENS Cachan - École normale supérieure - Cachan - CNRS - Centre National de la Recherche Scientifique
Hassan Maatouk: ENSM ST-ETIENNE - Ecole Nationale Supérieure des Mines de St Etienne

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Abstract: This paper collects the contributions which were presented during the session devoted to Gaussian processes at the Journées MAS 2016. First, an introduction to Gaussian processes is provided, and some current research questions are discussed. Then, an application of Gaussian process modeling under linear inequality constraints to financial data is presented. Also, an original procedure for handling large data sets is described. Finally, the case of Gaussian process based iterative optimization is discussed.

Date: 2017
Note: View the original document on HAL open archive server: https://hal.science/hal-01665936v1
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Published in ESAIM: Proceedings and Surveys, 2017, 60, pp.163-179. ⟨10.1051/proc/201760163⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01665936

DOI: 10.1051/proc/201760163

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