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Victor Picheny
Victor Picheny
Director of Research, Secondmind
E-mail confirmado em secondmind.ai - Página inicial
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A benchmark of kriging-based infill criteria for noisy optimization
V Picheny, T Wagner, D Ginsbourger
Structural and multidisciplinary optimization 48, 607-626, 2013
4662013
Sequential design of computer experiments for the estimation of a probability of failure
J Bect, D Ginsbourger, L Li, V Picheny, E Vazquez
Statistics and Computing 22, 773-793, 2012
4012012
Adaptive designs of experiments for accurate approximation of a target region
V Picheny, D Ginsbourger, O Roustant, RT Haftka, NH Kim
3742010
Quantile-based optimization of noisy computer experiments with tunable precision
V Picheny, D Ginsbourger, G Richet, Yann, Caplin
Technometrics, 2013
289*2013
Fast parallel kriging-based stepwise uncertainty reduction with application to the identification of an excursion set
C Chevalier, J Bect, D Ginsbourger, E Vazquez, V Picheny, Y Richet
Technometrics 56 (4), 455-465, 2014
1892014
Multiobjective optimization using Gaussian process emulators via stepwise uncertainty reduction
V Picheny
Statistics and Computing 25 (6), 1265-1280, 2015
1652015
On information gain and regret bounds in gaussian process bandits
S Vakili, K Khezeli, V Picheny
International Conference on Artificial Intelligence and Statistics, 82-90, 2021
1562021
Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian
V Picheny, RB Gramacy, S Wild, S Le Digabel
Advances in neural information processing systems 29, 2016
1282016
Comparison of kriging-based algorithms for simulation optimization with heterogeneous noise
H Jalali, I Van Nieuwenhuyse, V Picheny
European Journal of Operational Research 261 (1), 279-301, 2017
1272017
Application of bootstrap method in conservative estimation of reliability with limited samples
V Picheny, NH Kim, RT Haftka
Structural and Multidisciplinary Optimization 41, 205-217, 2010
1002010
A stepwise uncertainty reduction approach to constrained global optimization
V Picheny
Artificial intelligence and statistics, 787-795, 2014
952014
Improving accuracy and compensating for uncertainty in surrogate modeling
V Picheny
Saint-Etienne, EMSE, 2009
692009
Noisy kriging-based optimization methods: a unified implementation within the DiceOptim package
V Picheny, D Ginsbourger
Computational Statistics & Data Analysis 71, 1035-1053, 2014
632014
Using cross validation to design conservative surrogates
FA C. Viana, V Picheny, RT Haftka
Aiaa Journal 48 (10), 2286-2298, 2010
562010
Gaussian process optimization with simulation failures: classification and convergence proof
F Bachoc, C Helbert, V Picheny
Journal of Global Optimization 2020, 2019
50*2019
Kriginv: An efficient and user-friendly implementation of batch-sequential inversion strategies based on kriging
C Chevalier, V Picheny, D Ginsbourger
Computational statistics & data analysis 71, 1021-1034, 2014
49*2014
A nonstationary space-time Gaussian process model for partially converged simulations
V Picheny, D Ginsbourger
SIAM/ASA Journal on Uncertainty Quantification 1 (1), 57-78, 2013
472013
Scalable Thompson sampling using sparse Gaussian process models
S Vakili, H Moss, A Artemev, V Dutordoir, V Picheny
Advances in neural information processing systems 34, 5631-5643, 2021
462021
GPareto: An R Package for Gaussian-Process-Based Multi-Objective Optimization and Analysis
M Binois, V Picheny
Journal of Statistical Software 89 (8), 2019
46*2019
TREGO: a trust-region framework for efficient global optimization
Y Diouane, V Picheny, RL Riche, ASD Perrotolo
Journal of Global Optimization 86 (1), 1-23, 2023
452023
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