Maxime Nicaise

MSc, Applied Mathematics — CentraleSupélec (Paris-Saclay). Interested in Machine Learning and Optimal Transport.

Publications and Preprints

  • M. Nicaise, Y. Bermudez, and S. M. Perlaza. “A Gauge-Fixed Sinkhorn Algorithm for Semi-Relaxed Optimal Transport”. Inria Research Report, 2026. [HAL] [GitHub]

  • M. Nicaise, Y. Bermudez, and S. M. Perlaza. “Equivalence of optimal transport problems to regularization on the family of f-divergences”. IEEE International Symposium on Information Theory (ISIT), Guangzhou, China, 2026. [arXiv]

  • M. Nicaise, Y. Bermudez, and S. M. Perlaza. “On optimal transport with f-divergence regularization”. Inria Research Report, 2026. [HAL]

Internship at INRIA

Sophia-Antipolis, France

I pursued a research internship at INRIA, at the intersection of Applied Mathematics, Machine Learning, and Optimal Transport. More precisely, my work focused on entropic optimal transport as well as the broader class of f-divergence–regularized frameworks, establishing theoretical correspondances between these problems. My focus then shifted to the computational aspects of semi-relaxed optimal transport.

Three-semester PDE research project

MICS laboratory, CentraleSupélec, France

Research project focusing on the generalization of PDE and Functional Analysis theories to rough boundary domains. Explored the Stokes system for fluids with fractal boundaries to establish well-posedness with Dirichlet conditions, and expanded Hodge decomposition results to rough boundary domains.

Last semester (EN) Last semester slides Second semester report First semester report