Adversarial Weighting for Domain Adaptation in Regression. - Antoine de Mathelin; Guillaume Richard; François Deheeger; Mathilde Mougeot; Nicolas Vayatis (ICTAI, 2021)

ADAPT : Awesome Domain Adaptation Python Toolbox. - Antoine de Mathelin; François Deheeger; Guillaume Richard; Mathilde Mougeot; Nicolas Vayatis (CoRR, 2021)

Discrepancy-Based Active Learning for Domain Adaptation. - Antoine de Mathelin; François Deheeger; Mathilde Mougeot; Nicolas Vayatis (ICLR, 2022)

Fast and Accurate Importance Weighting for Correcting Sample Bias. - Antoine de Mathelin; François Deheeger; Mathilde Mougeot; Nicolas Vayatis (ECML/PKDD (1), 2022)

Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification. - Antoine de Mathelin; François Deheeger; Mathilde Mougeot; Nicolas Vayatis (CoRR, 2023)

Maximum Weight Entropy. - Antoine de Mathelin; François Deheeger; Mathilde Mougeot; Nicolas Vayatis (CoRR, 2023)

Unsupervised Representation Learning for Smart Transportation. - Thabang Lebese; Cécile Mattrand; David Clair; Jean-Marc Bourinet; François Deheeger (IDA (2), 2024)

OneBatchPAM: A Fast and Frugal K-Medoids Algorithm. - Antoine de Mathelin; Nicolas Enrique Cecchi; François Deheeger; Mathilde Mougeot; Nicolas Vayatis (AAAI, 2025)