Transport-based counterfactual models L De Lara, A González-Sanz, N Asher, L Risser, JM Loubes Journal of Machine Learning Research 25 (136), 1-59, 2024 | 40 | 2024 |
Counterfactual models for fair and adequate explanations N Asher, L De Lara, S Paul, C Russell Machine Learning and Knowledge Extraction 4 (2), 316-349, 2022 | 17 | 2022 |
Diffeomorphic registration using Sinkhorn divergences L De Lara, A González-Sanz, JM Loubes SIAM Journal on Imaging Sciences 16 (1), 250-279, 2023 | 14 | 2023 |
A consistent extension of discrete optimal transport maps for machine learning applications L De Lara, A González-Sanz, JM Loubes arXiv preprint arXiv:2102.08644, 2021 | 10 | 2021 |
GAN estimation of Lipschitz optimal transport maps A González-Sanz, L De Lara, L Béthune, JM Loubes arXiv preprint arXiv:2202.07965, 2022 | 4 | 2022 |
A clarification on the links between potential outcomes and do-interventions L De Lara arXiv preprint arXiv:2309.05997, 2023 | 3* | 2023 |
Modèles contrefactuels pour un apprentissage machine explicable et juste: une approche par transport de masse L de Lara Université Paul Sabatier-Toulouse III, 2023 | 1 | 2023 |
On the nonconvexity of push-forward constraints and its consequences in machine learning L De Lara, M Deronzier, A González-Sanz, V Foy arXiv preprint arXiv:2403.07471, 2024 | | 2024 |