The list of my publications can be found in   Google Scholar

Some main Publications by topics

Fairness in AI

• De Lara, L., González-Sanz, A., Asher, N., Risser, L., & Loubes, J. M. (2024). Transport-based counterfactual models. arXiv preprint arXiv:2108.13025.  to appear JMLR.
• Gordaliza, P., Del Barrio, E., Fabrice, G., & Loubes, J. M. (2019, May). Obtaining fairness using optimal transport theory. In International conference on machine learning (pp. 2357-2365). PMLR.
• Serrurier, M., Mamalet, F., González-Sanz, A., Boissin, T., Loubes, J. M., & Del Barrio, E. (2021). Achieving robustness in classification using optimal transport with hinge regularization. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 505-514).
• Bachoc, F., Gamboa, F., Halford, M., Loubes, J. M., & Risser, L. (2023). Explaining machine learning models using entropic variable projection. Information and Inference: A Journal of the IMA, 12(3), 1686-1715.
• Besse, P., del Barrio, E., Gordaliza, P., Loubes, J. M., & Risser, L. (2022). A survey of bias in machine learning through the prism of statistical parity. The American Statistician, 76(2), 188-198.

CLT on optimal transport

• del Barrio, E., & Loubes, J. M. (2019). CENTRAL LIMIT THEOREMS FOR EMPIRICAL TRANSPORTATION COST IN GENERAL DIMENSION. The Annals of Probability, 47(2), 926-951.
• del Barrio, E., González Sanz, A., & Loubes, J. M. (2024). Central limit theorems for semi-discrete Wasserstein distances. Bernoulli, 30(1), 554-580
• del Barrio, E., Sanz, A. G., Loubes, J. M., & Niles-Weed, J. (2023). An improved central limit theorem and fast convergence rates for entropic transportation costs. SIAM Journal on Mathematics of Data Science, 5(3), 639-669.

 Consistency  of empirical Wasserstein barycenters

• E. Boissard, T. Le Gouic, and J.-M. Loubes. Distribution’s template estimate with
  Wasserstein metrics. Bernoulli, 21(2) :740{759, 2015.
• T. Le Gouic and J.-M. Loubes. Existence and consistency of wasserstein barycenters.
  Probability Theory and Related Fields, 168(3-4) :901{917, 2017.

 Some Industrial Results on anomaly detection, road traffic and forecast

• P. C. Besse, B. Guillouet, J. M. Loubes, and F. Royer. Review and perspective for
  distance-based clustering of vehicle trajectories. IEEE Transactions on Intelligent
  Transportation Systems, PP(99) :1{12, 2016.
• C. Dimeglio, S. Gallon, J.-M. Loubes, and E. Maza. A robust algorithm for template
  curve estimation based on manifold embedding. Comput. Statist. Data Anal., 70 :373{
  386, 2014.
• J.-M. Loubes, E. Maza, M. Lavielle, and L. Rodrguez. Road tracking description
  and short term travel time forecasting, with a classication method. Canad. J.
  Statist., 34(3) :475{491, 2006.
• J. LOUBES, P. BESSE, A. CHOURY, B. GANDARD, and M. DUVERNIER.
  Procede de prediction de la vitesse d’un conducteur au volant d’un vehicule, Dec. 12
  2016. WO Patent App. PCT/FR2016/0970,037.
• A. BRUNET, J. LOUBES, J. AZAIS, and M. Courtney. Method of identication
  of a relationship between biological elements, Dec. 3 2015. WO Patent App.
  PCT/EP2015/060,779.
• J. LOUBES, F. GAMBOA, J. KIEN, and G. ALLAIN. Methode d’estimation d’un
  temps de parcours d’un vehicule dans un reseau routier, Dec. 27 2013. WO Patent
  App. PCT/FR2013/051,423.
• Grimaldi, B., Bremond, F., Cote, R., Bosch, T., Bony, F., & Loubes, J. M. (2023). U.S. Patent Application No. 17/921,716.

 Applications to Paelanthropolgy

• J Braga, JM Loubes. Disproportionate cochlear length in genus homo shows a high
  phylogenetic signal during apes ? hearing evolution. PloS one, 10(6) :e0127780, 2015.
• J. Braga, J. F. Thackeray, J. Dumoncel, D. Descouens, L. Bruxelles, J.-M. Loubes,
  J.-L. Kahn, M. Stampanoni, L. Bam, J. Homan, et al. A new partial temporal bone
  of a juvenile hominin from the site of kromdraai b (south africa). Journal of human
  evolution, 65(4) :447{456, 2013.