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4 papers · 2 filters
Uncertainty quantification in a mechanical submodel driven by a Wasserstein-GAN
Hamza Boukraichi, Nissrine Akkari, Fabien Casenave +1
The analysis of parametric and non-parametric uncertainties of very large dynamical systems requires the construction of a stochastic model of said system. Linear approaches relyin…
SHAFF: Fast and consistent SHApley eFfect estimates via random Forests
Clément Bénard, Gérard Biau, Sébastien da Veiga +1
Interpretability of learning algorithms is crucial for applications involving critical decisions, and variable importance is one of the main interpretation tools. Shapley effects a…
MDA for random forests: inconsistency, and a practical solution via the Sobol-MDA
Clément Bénard, Sébastien da Veiga, Erwan Scornet
Variable importance measures are the main tools to analyze the black-box mechanisms of random forests. Although the mean decrease accuracy (MDA) is widely accepted as the most effi…
Data augmentation and feature selection for automatic model recommendation in computational physics
Thomas Daniel, Fabien Casenave, Nissrine Akkari +1
Classification algorithms have recently found applications in computational physics for the selection of numerical methods or models adapted to the environment and the state of the…