Faculté des Sciences et Technologies
Trustworthy machine learning
Machine Learning, Optimal Transport, Causality, Fairness
IECL – Site de Nancy
Faculté des sciences et Technologies
Campus, Boulevard des Aiguillettes
54506 Vandœuvre-lès-Nancy
Pour la version française c’est par ici !
My research focuses on trustworthy machine learning using tools from optimal-transport theory and causal inference.
I’m currently a postdoctoral researcher in applied mathematics at IECL and CRAN (Nancy, France), investigating various aspects of causality and machine learning with Marianne Clausel.
Before that, I did my PhD at IMT (Toulouse, France) on fair machine learning and optimal transport with Jean-Michel Loubes and Laurent Risser.
My CV updated on December 1, 2024.
Check my Google Scholar and Github for the manuscripts and the codes
Publications
[1] 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)
[2] Diffeomorphic registration using Sinkhorn divergences, L De Lara, A González-Sanz, JM Loubes, SIAM Journal on Imaging Sciences 16 (1), 250-279 (2023)
[3] 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)
Preprints
[1] On the nonconvexity of push-forward constraints and its consequences in machine learning, L De Lara, M Deronzier, A González-Sanz, V Foy, Under review (2024)
[2] A clarification on the links between potential outcomes and do-interventions, L De Lara, Under review (2024)
[3] GAN estimation of Lipschitz optimal transport maps, A González-Sanz, L De Lara, L Béthune, JM Loubes (2022)
- 2023 – 2024 : Research and teaching assistant at Université Paul Sabatier
- 2020 – 2023 : PhD in applied mathematics at Université Paul Sabatier
- 2019 – 2020 : M2 in statistics and machine learning at Université Paris-Saclay
- 2016 – 2019 : Ecole polytechnique (major in applied mathematics)