On the use of SMC methods in the sequential design of computer experiments

Bayesian multi-objective optimization with noisy evaluations

Bayesian multi-objective optimization with noisy evaluations using the Knowledge Gradient

Gaussian process model selection for computer experiments

Bayesian Subset Simulation Tutorial

Quantification et réduction de l'incertitude concernant les propriétés de monotonie d'un code de calcul coûteux à évaluer

Perturbed-Law based sensitivity Indices for sensitivity analysis in structural reliability

BMOO: a Bayesian Multi-Objective Optimization algorithm

Rational kernel-based interpolation for complex-valued frequency response functions

Bayesian multi-objective optimization for stochastic simulators: an extension of the Pareto Active Learning method

Bayesian multi-objective optimization with constraints: Application to the design of a commercial aircraft environment control system

Uncertainty quantification and reduction for the monotonicity properties of expensive-to-evaluate computer models

A Bayesian approach for the optimal integration of renewable energy sources in distribution networks over multi-year horizons

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

A Bayesian Approach to Constrained Multi-objective Optimization

Estimating and quantifying uncertainties on level sets using the Vorob'ev expectation and deviation with Gaussian process models

Learning of Frequency Response Functions in Electrical Engineering

Bias and Variance in the Bayesian Subset Simulation Algorithm

Estimation of Small Quantile Sets Using a Sequential Bayesian Strategy

Bayesian subset simulation

Quantifying uncertainties on excursion sets under a Gaussian random field prior

Gaussian Process Regression for Complex-Valued Frequency Response Functions

Active Learning of (small) Quantile Sets

Sequential design of experiments to estimate a probability of exceeding a threshold in a multi-fidelity stochastic simulator

Extension of the Pareto Active Learning method to multi-objective optimization for stochastic simulators

Reliability-based inversion: Stepwise uncertainty reduction strategies?

Numerical issues in maximum likelihood parameter estimation for Gaussian process interpolation

Bayesian multi-objective optimization for stochastic simulators

Assessing fire safety using complex numerical models with a Bayesian multi-fidelity approach

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

Planification et analyse d’expériences numériques, appliquées à la sécurité en ingénierie incendie

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

A Bayesian approach to constrained multi-objective optimization of expensive-to-evaluate functions

A Bayesian approach to constrained multi-objective optimization

Stepwise Entropy Reduction : Review of Theoretical Results in the Finite/Deterministic case

Sequential design of multi-fidelity computer experiments: maximizing the rate of stepwise uncertainty reduction

Bayesian sequential design of computer experiments for quantile set inversion

Approche bayésienne pour l'estimation d'indices de Sobol

Multipathogen quantitative risk assessment in raw milk soft cheese

Adaptive Design of Experiments for Conservative Estimation of Excursion Sets

A Bayesian approach to constrained single- and multi-objective optimization

Planification d’expériences numériques en multi-fidélité, appliquée à la sécurité en ingénierie incendie

Integration of bounded monotone functions: Revisiting the nonsequential case, with a focus on unbiased Monte Carlo (randomized) methods

Échantillonnage préférentiel et méta-modèles : méthodes bayésiennes optimale et défensive

Gaussian process modeling for stochastic multi-fidelity simulators, with application to fire safety

Adaptive Design of Experiments for Conservative Estimation of Excursion Sets

A novel non-intrusive method using design of experiments and smooth approximation to speed up multi-period load-flows in distribution network planning

On the quantification of discretization uncertainty: comparison of two paradigms