Publications

Parameter influence analysis in a 3D TBM model via sensitivity analysis and Gaussian process metamodels

Bayesian sequential design of computer experiments for quantile set inversion

A Bayesian framework for calibrating Gaussian process predictive distributions

Goal-oriented calibration of Gaussian Processes with conformal prediction

Bayesian Active Learning of (small) Quantile Sets through Expected Estimator Modification

Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization

Quantitative risk assessment of Haemolytic and Uremic Syndrome (HUS) from consumption of raw milk soft cheese

Multipathogen quantitative risk assessment in raw milk soft cheese

Active Learning of (small) Quantile Sets

Gaussian process interpolation with conformal prediction: methods and comparative analysis

A stepwise uncertainty reduction strategy for the estimation of small quantile sets

Estimation of Small Quantile Sets Using a Sequential Bayesian Strategy

Multi-output Gaussian process for river water height estimation

Scalable Gaussian Process for Large Datasets

Numerical study of the calibration of predictive distributions from Gaussian process interpolation

Parameter selection in Gaussian process interpolation: An empirical study of selection criteria

Minimizing the risk of foodborne illness and analytical costs using a QMRA model for raw milk cheeses

Kriging metamodels for 2D finite element simulations of the settlements induced by TBM excavation in urban areas

Bayesian multi-objective optimization for stochastic simulators

Optimizing TBM Parameters through Surface Settlement Monitoring Using Surrogate Modelling Approach

Estimation of (small) reliable sets using a sequential Bayesian strategy

MINERVE – Un jumeau numérique pour gérer l’infrastructure ferroviaire

STK: a Small (Matlab/Octave) Toolbox for Kriging

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?

Quantitative risk assessment and optimization of process intervention parameters for French raw milk soft cheese

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

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

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

Integrating hyper-parameter uncertainties in a multi-fidelity Bayesian model for the estimation of a probability of failure

Bayesian subset simulation

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

Bayesian Optimization

Sequential search strategies based on kriging

Modélisation comportementale de systèmes non-linéaires multivariables par méthodes à noyaux et applications