
Global sensitivity analysis using derivativebased sparse Poincaré chaos expansions
Variancebased global sensitivity analysis, in particular Sobol' analysi...
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Fairness seen as Global Sensitivity Analysis
Ensuring that a predictor is not biased against a sensible feature is th...
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Weighted lens depth: Some applications to supervised classification
Starting with Tukey's pioneering work in the 1970's, the notion of depth...
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Dual optimal design and the ChristoffelDarboux polynomial
The purpose of this short note is to show that the ChristoffelDarboux p...
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Global Sensitivity Analysis: a new generation of mighty estimators based on rank statistics
We propose a new statistical estimation framework for a large family of ...
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Sensitivity analysis in general metric spaces
In this paper, we introduce new indices adapted to outputs valued in gen...
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Optimal Uncertainty Quantification of a risk measurement from a thermalhydraulic code using Canonical Moments
We study an industrial computer code related to nuclear safety. A major ...
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Optimal Uncertainty Quantification on moment class using canonical moments
We gain robustness on the quantification of a risk measurement by accoun...
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Entropic Variable Boosting for Explainability and Interpretability in Machine Learning
In this paper, we present a new explainability formalism to make clear t...
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Obtaining fairness using optimal transport theory
Statistical algorithms are usually helping in making decisions in many a...
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Gaussian Processes indexed on the symmetric group: prediction and learning
In the framework of the supervised learning of a real function defined o...
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Deep Learning applied to Road Traffic Speed forecasting
In this paper, we propose deep learning architectures (FNN, CNN and LSTM...
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Gaussian Process Regression Model for Distribution Inputs
MongeKantorovich distances, otherwise known as Wasserstein distances, h...
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Modeling Weather Conditions Consequences on Road Trafficking Behaviors
We provide a model to understand how adverse weather conditions modify t...
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Fabrice Gamboa
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