44 citations · 85 across the 6 of their papers we have counts for
9 papers
Uncertainty and sensitivity analysis of functional risk curves based on Gaussian processes
Bertrand Iooss, Loïc Le Gratiet
A functional risk curve gives the probability of an undesirable event as a function of the value of a critical parameter of a considered physical system. In several applicative sit…
Model Assisted Probability of Detection curves: New statistical tools and progressive methodology
Loïc Le Gratiet, Bertrand Iooss, Géraud Blatman +3
The Probability Of Detection (POD) curve is a standard tool in several industries to evaluate the performance of Non Destructive Testing (NDT) procedures for the detection of harmf…
Stochastic simulators based optimization by Gaussian process metamodels -- Application to maintenance investments planning issues
Thomas Browne, Bertrand Iooss, Loïc Le Gratiet +2
This paper deals with the optimization of industrial asset management strategies, whose profitability is characterized by the Net Present Value (NPV) indicator which is assessed by…
Stochastic simulators based optimization by Gaussian process metamodels - Application to maintenance investments planning issues
Thomas Browne, Bertrand Iooss, Loïc Le Gratiet +1
This paper deals with the construction of a metamodel (i.e. a simplified mathematical model) for a stochastic computer code (also called stochastic numerical model or stochastic si…
ANOVA decomposition of conditional Gaussian processes for sensitivity analysis with dependent inputs
Gaëlle Chastaing, Loic Le Gratiet
Complex computer codes are widely used in science to model physical systems. Sensitivity analysis aims to measure the contributions of the inputs on the code output variability. An…
A Bayesian approach for global sensitivity analysis of (multi-fidelity) computer codes
Loic Le Gratiet, Claire Cannamela, Bertrand Iooss
Complex computer codes are widely used in science and engineering to model physical phenomena. Furthermore, it is common that they have a large number of input parameters. Global s…
Asymptotic normality of a Sobol index estimator in Gaussian process regression framework
Loic Le Gratiet
Stochastic simulators such as Monte-Carlo estimators are widely used in science and engineering to study physical systems through their probabilistic representation. Global sensiti…
Planification d'expériences séquentielle dans un contexte de méta-modélisation multi-fidélité
Loic Le Gratiet
Large computer codes are widely used in engineering to study physical systems. Nevertheless, simulations can sometimes be time-consuming. In this case, an approximation of the code…
Bayesian analysis of hierarchical multi-fidelity codes
Loic Le Gratiet
This paper deals with the Gaussian process based approximation of a code which can be run at different levels of accuracy. This method, which is a particular case of co-kriging, al…