16 citations · 23 across the 10 of their papers we have counts for
5 papers · 1 filter
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…
Kernel Stein Discrepancy thinning: a theoretical perspective of pathologies and a practical fix with regularization
Clément Bénard, Brian Staber, Sébastien Da Veiga
Stein thinning is a promising algorithm proposed by (Riabiz et al., 2022) for post-processing outputs of Markov chain Monte Carlo (MCMC). The main principle is to greedily minimize…
Global Sensitivity Analysis with Dependence Measures
Sébastien Da Veiga
Global sensitivity analysis with variance-based measures suffers from several theoretical and practical limitations, since they focus only on the variance of the output and handle…
Efficient Estimation of Sensitivity Indices
Sébastien Da Veiga, Fabrice Gamboa
In this paper we address the problem of efficient estimation of Sobol sensitivy indices. First, we focus on general functional integrals of conditional moments of the form $\E(ψ(\E…
Efficient estimation of conditional covariance matrices for dimension reduction
Sébastien Da Veiga, Jean-Michel Loubes, Maikol Solís
Let and . In this paper we propose an estimator of the conditional covariance matrix, $\mathrm{Cov}(\mathbb{E}[\boldsymbol{X}\vert…