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
Kriging metamodels for 2D finite element simulations of the settlements induced by TBM excavation in urban areas
Optimizing TBM Parameters through Surface Settlement Monitoring Using Surrogate Modelling Approach
MINERVE – Un jumeau numérique pour gérer l’infrastructure ferroviaire
Parameter selection in Gaussian process interpolation: an empirical study of selection criteria
Bayesian sequential design of computer experiments for quantile set inversion
Sequential design of multi-fidelity computer experiments: maximizing the rate of stepwise uncertainty reduction
Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization
Reliability-based inversion: Stepwise uncertainty reduction strategies?
Integration of bounded monotone functions: Revisiting the nonsequential case, with a focus on unbiased Monte Carlo (randomized) methods
Bayesian multi-objective optimization for quantitative risk assessment in microbiology
Sequential Bayesian inversion of black-box functions in presence of uncertainties
Bayesian multi-objective optimization for stochastic simulators: an extension of the Pareto Active Learning method
Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization
Numerical issues in maximum likelihood parameter estimation for Gaussian process interpolation
A Bayesian approach for the optimal integration of renewable energy sources in distribution networks over multi-year horizons
Towards new cross-validation-based estimators for Gaussian process regression: efficient adjoint computation of gradients
Extension of the Pareto Active Learning Method to Multi-Objective Optimization for Stochastic Simulators
Extension of the Pareto Active Learning method to multi-objective optimization for stochastic simulators
On the quantification of discretization uncertainty: comparison of two paradigms
Bayesian multi-objective optimization with noisy evaluations
Gaussian process model selection for computer experiments
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
Bayesian Subset Simulation Tutorial
Planification d’expériences numériques en multi-fidélité, appliquée à la sécurité en ingénierie incendie
User preferences in Bayesian multi-objective optimization: the expected weighted hypervolume improvement criterion
Bayesian subset simulation
Assessing fire safety using complex numerical models with a Bayesian multi-fidelity approach
A Bayesian approach to constrained single- and multi-objective optimization
User preferences in Bayesian multi-objective optimization
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
Sequential design of experiment on a stochastic multi-fidelity simulator to estimate a probability of exceeding a threshold
Design of a commercial aircraft environment control system using Bayesian optimization techniques
Bayesian Optimization
Planification et analyse d’expériences numériques, appliquées à la sécurité en ingénierie incendie
BMOO: a Bayesian Multi-Objective Optimization algorithm
Bias and Variance in the Bayesian Subset Simulation Algorithm
Gaussian process modeling for stochastic multi-fidelity simulators, with application to fire safety
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
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
A Bayesian approach to constrained multi-objective optimization of expensive-to-evaluate functions
A Bayesian Approach to Constrained Multi-objective Optimization
Sequential search strategies based on kriging
A Bayesian approach to constrained multi-objective optimization
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
Sequential search strategies based on kriging
Modélisation comportementale de systèmes non-linéaires multivariables par méthodes à noyaux et applications