57 citations · 80 across the 4 of their papers we have counts for
5 papers
A Bayesian neural network approach to Multi-fidelity surrogate modelling
Baptiste Kerleguer, Claire Cannamela, Josselin Garnier
This paper deals with surrogate modelling of a computer code output in a hierarchical multi-fidelity context, i.e., when the output can be evaluated at different levels of accuracy…
On the quantification of discretization uncertainty: comparison of two paradigms
Julien Bect, Souleymane Zio, Guillaume Perrin +2
Numerical models based on partial differential equations (PDE), or integro-differential equations, are ubiquitous in engineering and science, making it possible to understand or de…
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…
Kriging-based sequential design strategies using fast cross-validation techniques with extensions to multi-fidelity computer codes
Loic Le Gratiet, Claire Cannamela
Kriging-based surrogate models have become very popular during the last decades to approximate a computer code output from few simulations. In practical applications, it is very co…
Controlled stratification for quantile estimation
Claire Cannamela, Josselin Garnier, Bertrand Iooss
In this paper we propose and discuss variance reduction techniques for the estimation of quantiles of the output of a complex model with random input parameters. These techniques a…