Antoine de Mathelin

22 papers A* 2B 2Journal 14Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
Empirically Calibrated Conditional Independence Tests.
CoRR
Milleno Pan, Antoine de Mathelin, Wesley Tansey
2025 — conf
Addressing the Cold-Start Problem for Personalized Combination Drug Screening.
MLCB
Antoine de Mathelin, Christopher Tosh, Wesley Tansey
2025 J jnl
Addressing the Cold-Start Problem for Personalized Combination Drug Screening.
CoRR
Antoine de Mathelin, Christopher Tosh, Wesley Tansey
2025 J jnl
Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization.
J. Mach. Learn. Res.
Antoine de Mathelin, François Deheeger, Mathilde Mougeot, Nicolas Vayatis
2025 A* conf
OneBatchPAM: A Fast and Frugal K-Medoids Algorithm.
AAAI
Antoine de Mathelin, Nicolas Enrique Cecchi, François Deheeger, Mathilde Mougeot, Nicolas Vayatis
2025 J jnl
OneBatchPAM: A Fast and Frugal K-Medoids Algorithm.
CoRR
Antoine de Mathelin, Nicolas Enrique Cecchi, François Deheeger, Mathilde Mougeot, Nicolas Vayatis
2025 J jnl
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities.
Trans. Mach. Learn. Res.
Yanis Lalou, Théo Gnassounou, Antoine Collas, Antoine de Mathelin, Ambroise Odonnat, Thomas Moreau, Alexandre Gramfort, Rémi Flamary
2024 J jnl
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation.
CoRR
Yanis Lalou, Théo Gnassounou, Antoine Collas, Antoine de Mathelin, Oleksii Kachaiev, Ambroise Odonnat, Alexandre Gramfort, Thomas Moreau, Rémi Flamary
2024 — —
Towards reliable machine learning under domain shift and costly labeling, with applications to engineering design. (Vers un apprentissage automatique fiable sous contrainte de changement de domaine et d'étiquetage coûteux. : Application à la conception produits).
Antoine de Mathelin
2023 J jnl
Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification.
CoRR
Antoine de Mathelin, François Deheeger, Mathilde Mougeot, Nicolas Vayatis
2023 J jnl
Maximum Weight Entropy.
CoRR
Antoine de Mathelin, François Deheeger, Mathilde Mougeot, Nicolas Vayatis
2023 B conf
Personalized One-Shot Collaborative Learning.
ICTAI
Marie Garin, Antoine de Mathelin, Mathilde Mougeot, Nicolas Vayatis
2022 A* conf
Discrepancy-Based Active Learning for Domain Adaptation.
ICLR
Antoine de Mathelin, François Deheeger, Mathilde Mougeot, Nicolas Vayatis
2022 — conf
Fast and Accurate Importance Weighting for Correcting Sample Bias.
ECML/PKDD (1)
Antoine de Mathelin, François Deheeger, Mathilde Mougeot, Nicolas Vayatis
2022 J jnl
Fast and Accurate Importance Weighting for Correcting Sample Bias.
CoRR
Antoine de Mathelin, François Deheeger, Mathilde Mougeot, Nicolas Vayatis
2021 J jnl
A Binded VAE for Inorganic Material Generation.
CoRR
Fouad Oubari, Antoine de Mathelin, Rodrigue Décatoire, Mathilde Mougeot
2021 J jnl
ADAPT : Awesome Domain Adaptation Python Toolbox.
CoRR
Antoine de Mathelin, François Deheeger, Guillaume Richard, Mathilde Mougeot, Nicolas Vayatis
2021 B conf
Adversarial Weighting for Domain Adaptation in Regression.
ICTAI
Antoine de Mathelin, Guillaume Richard, François Deheeger, Mathilde Mougeot, Nicolas Vayatis
2021 J jnl
Discrepancy-Based Active Learning for Domain Adaptation.
CoRR
Antoine de Mathelin, Mathilde Mougeot, Nicolas Vayatis
2021 J jnl
Unsupervised Domain Adaptation for Constraining Star Formation Histories.
CoRR
Sankalp Gilda, Antoine de Mathelin, Sabine Bellstedt, Guillaume Richard
2020 J jnl
Adversarial Weighting for Domain Adaptation in Regression.
CoRR
Antoine de Mathelin, Guillaume Richard, Mathilde Mougeot, Nicolas Vayatis
2020 — conf
Unsupervised Multi-source Domain Adaptation for Regression.
ECML/PKDD (1)
Guillaume Richard, Antoine de Mathelin, Georges Hébrail, Mathilde Mougeot, Nicolas Vayatis