I graduated from École Centrale de Lille with major in data science and now working on Optimal Transport. More precisely my objective is to include the inherent structural information of usual machine learning objects (graph, time series…) in the Optimal Transportation problem and to use this new formulation for the classification of structured data.
Publications & Talks
- Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical properties : recent paper available on ArXiV
- Optmimal Transport for Structured Data : available on ArXiV.
- Juin 2018 : “Fused Gromov Wasserstein Distance” at CAp Conference
- Ecole Centrale de Nantes (ECN) October 2018 : Generative models (GAN’s, Wasserstein GAN’s and VAE), all materials available on my GitHub
- E-mail: email@example.com
- Phone: +33 (0)6 82 32 55 70
- Office: Somewhere in Vannes, somewhere in France