Céline Helbert

Gradient-based active learning with Gaussian processes for global sensitivity analysis.

Global sensitivity analysis of complex numerical simulators is often limited by the small number of model evaluations that can be afforded. In such settings, surrogate models built from a limited set of simulations can substantially reduce the computational burden, provided that...

Active learning strategies for the estimation of a feasible set defined from a vector output black-box simulator

Many industrial problems require the use of black-box numerical simulators, for which it is essential to determine the set of so-called feasible input parameters. A set of parameters is feasible if the output of the code on these parameters satisfies given constraints, for exampl...