Publications

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