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Sébastien J. Petit
Sébastien J. Petit
LNE
Verified email at lne.fr
Title
Cited by
Cited by
Year
Numerical issues in maximum likelihood parameter estimation for Gaussian process interpolation
S Basak, S Petit, J Bect, E Vazquez
7th International Conference on machine Learning, Optimization and Data …, 2021
22*2021
Parameter selection in Gaussian process interpolation: an empirical study of selection criteria
SJ Petit, J Bect, P Feliot, E Vazquez
SIAM/ASA Journal on Uncertainty Quantification 11 (4), 1308-1328, 2023
7*2023
Towards new cross-validation-based estimators for Gaussian process regression: efficient adjoint computation of gradients
S Petit, J Bect, S da Veiga, P Feliot, E Vazquez
Journées de Statistiques 2020, 2020
62020
Échantillonnage préférentiel et méta-modèles: méthodes bayésiennes optimale et défensive
J Bect, R Sueur, A Gérossier, L Mongellaz, S Petit, E Vazquez
47èmes Journées de Statistique de la SFdS (JdS 2015), 2015
52015
Improved Gaussian process modeling: Application to Bayesian optimization
S Petit
Université Paris-Saclay, 2022
42022
An asymptotic study of the joint maximum likelihood estimation of the regularity and the amplitude parameters of a Matérn model on the circle
S Petit
arXiv preprint arXiv:2209.07791, 2023
3*2023
Couplage entre indices à base de dérivées et mode adjoint pour l'analyse de sensibilité globale. Application sur le code Mascaret
S Petit, F Zaoui, AL Popelin, C Goeury, N Goutal
Unpublished manuscript, 2016
3*2016
Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization
S Petit, J Bect, E Vazquez
arXiv preprint arXiv:2206.03034, 2022
22022
Input uncertainty propagation through trained neural networks
P Monchot, L Coquelin, SJ Petit, S Marmin, E Le Pennec, N Fischer
International Conference on Machine Learning, 25140-25173, 2023
12023
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