Emmanuel VAZQUEZ
Prof. & researcher in Bayesian design and analysis of computer experiments; coordinator of Data Science projects at CentraleSupelec
emmanuel.vazquez@l2s.centralesupelec.fr
L2S, CentraleSupélec
Bât. Breguet A3.20
3 rue Joliot Curie
91190 Gif-sur-Yvette, France
MINERVE – Un jumeau numérique pour gérer l’infrastructure ferroviaire
Sequential design of multi-fidelity computer experiments: maximizing the rate of stepwise uncertainty reduction
Integration of bounded monotone functions: Revisiting the nonsequential case, with a focus on unbiased Monte Carlo (randomized) methods
Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization
Reliability-based inversion: Stepwise uncertainty reduction strategies?
Bayesian multi-objective optimization for quantitative risk assessment in microbiology
Sequential Bayesian inversion of black-box functions in presence of uncertainties
Parameter selection in Gaussian process interpolation: an empirical study of selection criteria
Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization
Bayesian multi-objective optimization for stochastic simulators: an extension of the Pareto Active Learning method
Bayesian sequential design of computer experiments to estimate reliable sets
Extension of the Pareto Active Learning method to multi-objective optimization for stochastic simulators
On the quantification of discretization uncertainty: comparison of two paradigms
Extension of the Pareto Active Learning Method to Multi-Objective Optimization for Stochastic Simulators
Towards new cross-validation-based estimators for Gaussian process regression: efficient adjoint computation of gradients
A Bayesian approach for the optimal integration of renewable energy sources in distribution networks over multi-year horizons
Numerical issues in maximum likelihood parameter estimation for Gaussian process interpolation
Gaussian process model selection for computer experiments
Bayesian multi-objective optimization with noisy evaluations
Bayesian multi-objective optimization with noisy evaluations using the Knowledge Gradient
Optimisation of multi-year planning strategies to better integrate renewable energies and new electricity uses in the distribution grid
User preferences in Bayesian multi-objective optimization: the expected weighted hypervolume improvement criterion
Planification d’expériences numériques en multi-fidélité, appliquée à la sécurité en ingénierie incendie
Bayesian Subset Simulation Tutorial
Assessing fire safety using complex numerical models with a Bayesian multi-fidelity approach
Bayesian subset simulation
A Bayesian approach to constrained single- and multi-objective optimization
Design of a commercial aircraft environment control system using Bayesian optimization techniques
Sequential design of experiment on a stochastic multi-fidelity simulator to estimate a probability of exceeding a threshold
Integrating hyper-parameter uncertainties in a multi-fidelity Bayesian model for the estimation of a probability of failure
Sequential design of experiments to estimate a probability of exceeding a threshold in a multi-fidelity stochastic simulator
User preferences in Bayesian multi-objective optimization
Bayesian Optimization
Gaussian process modeling for stochastic multi-fidelity simulators, with application to fire safety
Bias and Variance in the Bayesian Subset Simulation Algorithm
BMOO: a Bayesian Multi-Objective Optimization algorithm
Planification et analyse d’expériences numériques, appliquées à la sécurité en ingénierie incendie
Design and analysis of multi-level numerical experiments, with application to fire safety
Bayesian multi-objective optimization with constraints: Application to the design of a commercial aircraft environment control system
A Bayesian approach to constrained multi-objective optimization of expensive-to-evaluate functions
A Bayesian Approach to Constrained Multi-objective Optimization
The Informational Approach to Global Optimization in presence of very noisy evaluation results. Application to the optimization of renewable energy integration strategies
Échantillonnage préférentiel et méta-modèles : méthodes bayésiennes optimale et défensive
Sequential search strategies based on kriging
A Bayesian approach to constrained multi-objective optimization
Fast parallel kriging-based stepwise uncertainty reduction with application to the identification of an excursion set
A Bayesian subset simulation approach to constrained global optimization of expensive-to-evaluate black-box functions
Quantification et réduction de l’incertitude concernant les propriétés de monotonie d’un code de calcul coûteux à évaluer
Uncertainty quantification and reduction for the monotonicity properties of expensive-to-evaluate computer models
Fully Bayesian approach for the estimation of (first-order) Sobol indices
Sequential search strategies based on kriging
Modélisation comportementale de systèmes non-linéaires multivariables par méthodes à noyaux et applications