19 citations · 88 across the 24 of their papers we have counts for
27 papers
A probabilistic reduced basis method for parameter-dependent problems
Marie Billaud-Friess, Arthur Macherey, Anthony Nouy +1
Probabilistic variants of Model Order Reduction (MOR) methods have recently emerged for improving stability and computational performance of classical approaches. In this paper, we…
Sensitivity analysis from a single input/output sample
Sébastien Da Veiga, Fabrice Gamboa, Thierry Klein +2
The main objective of this paper is to estimate optimally Sobol' indices at any order when a unique input/output i.i.d.\ sample is available. Our approach stands on three main ingr…
Variance-based global sensitivity analysis of numerical models using R
Hossein Mohammadi, Peter Challenor, Clémentine Prieur
Sensitivity analysis plays an important role in the development of computer models/simulators through identifying the contribution of each (uncertain) input factor to the model out…
Performing global sensitivity analysis on simulations of a continuous-time Markov chain model motivated by epidemiology
Henri Mermoz Kouye, Gildas Mazo, Clémentine Prieur +1
In this paper we apply a methodology introduced in Navarro Jimenez et al (2016) in the framework of chemical reaction networks to perform a global sensitivity analysis on simulatio…
A probabilistic point of view for the Kolmogorov hypoelliptic equations
Pierre Etoré, Jose R León, Clémentine Prieur
In this work, we propose a method for solving Kolmogorov hypoelliptic equations based on Fourier transform and Feynman-Kac formula. We first explain how the Feynman-Kac formula can…
Nonlinear dimension reduction for surrogate modeling using gradient information
Daniele Bigoni, Youssef Marzouk, Clémentine Prieur +1
We introduce a method for the nonlinear dimension reduction of a high-dimensional function , . Our objective is to identify a nonlinear…