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Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization

Sébastien Petit 1, 2, 3 Julien Bect 2, 3 Emmanuel Vazquez 2, 3 
1 Safran Aircraft Engines
2 L2S - Laboratoire des signaux et systèmes
3 GdR MASCOT-NUM - Méthodes d'Analyse Stochastique des Codes et Traitements Numériques
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Conference papers
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https://hal-centralesupelec.archives-ouvertes.fr/hal-03715755
Contributor : Julien Bect Connect in order to contact the contributor
Submitted on : Wednesday, July 6, 2022 - 5:18:30 PM
Last modification on : Sunday, July 24, 2022 - 3:22:53 AM

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Distributed under a Creative Commons Attribution - NonCommercial - NoDerivatives 4.0 International License

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  • HAL Id : hal-03715755, version 1

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CNRS | SUP_LSS | CENTRALESUPELEC | UNIV-PARIS-SACLAY | GS-ENGINEERING | GS-COMPUTER-SCIENCE | HUB-IA

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Sébastien Petit, Julien Bect, Emmanuel Vazquez. Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization. MASCOT-NUM 2022, Jun 2022, Clermont-Ferrand, France. ⟨hal-03715755⟩

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