In this work, we develop an approach mentioned by da Veiga and Gamboa in...
Stein thinning is a promising algorithm proposed by (Riabiz et al., 2022...
Interpretability of learning algorithms is crucial for applications invo...
We consider the problem of chance constrained optimization where it is s...
Variable importance measures are the main tools to analyze the black-box...
Global sensitivity analysis is the main quantitative technique for
ident...
We introduce SIRUS (Stable and Interpretable RUle Set) for regression, a...
We consider the problem of estimating the parameters of the covariance
f...
State-of-the-art learning algorithms, such as random forests or neural
n...
The optimization of high dimensional functions is a key issue in enginee...
Global sensitivity analysis with variance-based measures suffers from se...