30 citations · 74 across the 20 of their papers we have counts for
7 papers · 1 filter
Generalized Oversampling for Learning from Imbalanced datasets and Associated Theory
Samuel Stocksieker, Denys Pommeret, Arthur Charpentier
In supervised learning, it is quite frequent to be confronted with real imbalanced datasets. This situation leads to a learning difficulty for standard algorithms. Research and sol…
Fairness Explainability using Optimal Transport with Applications in Image Classification
Philipp Ratz, François Hu, Arthur Charpentier
Ensuring trust and accountability in Artificial Intelligence systems demands explainability of its outcomes. Despite significant progress in Explainable AI, human biases still tain…
Fairness in Multi-Task Learning via Wasserstein Barycenters
François Hu, Philipp Ratz, Arthur Charpentier
Algorithmic Fairness is an established field in machine learning that aims to reduce biases in data. Recent advances have proposed various methods to ensure fairness in a univariat…
Mitigating Discrimination in Insurance with Wasserstein Barycenters
Arthur Charpentier, François Hu, Philipp Ratz
The insurance industry is heavily reliant on predictions of risks based on characteristics of potential customers. Although the use of said models is common, researchers have long…
Optimal Vaccination Policy to Prevent Endemicity: A Stochastic Model
Félix Foutel-Rodier, Arthur Charpentier, Hélène Guérin
We examine here the effects of recurrent vaccination and waning immunity on the establishment of an endemic equilibrium in a population. An individual-based model that incorporates…
Data Augmentation for Imbalanced Regression
Samuel Stocksieker, Denys Pommeret, Arthur Charpentier
In this work, we consider the problem of imbalanced data in a regression framework when the imbalanced phenomenon concerns continuous or discrete covariates. Such a situation can l…
Optimal Transport for Counterfactual Estimation: A Method for Causal Inference
Arthur Charpentier, Emmanuel Flachaire, Ewen Gallic
Many problems ask a question that can be formulated as a causal question: "what would have happened if...?" For example, "would the person have had surgery if he or she had been Bl…