My PhD manuscript can be found here, and the slides of the defense here.

Preprints and working papers

Boris Muzellec, Adrien Vacher, Francis Bach, François-Xavier Vialard and Alessandro Rudi. Near-optimal estimation of smooth transport maps with kernel sums-of-squares, arXiv preprint, 2021. [Paper]

Boris Muzellec, Francis Bach and Alessandro Rudi. Learning PSD-valued functions using kernel sums-of-squares, arXiv preprint, 2021. [Paper]


Jean Ogier du Terrail et al. FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings, NeurIPS Datasets & Benchmarks 2022. [Paper] [Code]

Tanguy Marchand, Boris Muzellec, Constance Beguier, Jean Ogier du Terrail, Mathieu Andreux. SecureFedYJ: a safe feature Gaussianization protocol for Federated Learning, NeurIPS 2022. [Paper]

Boris Muzellec, Kanji Sato, Mathurin Massias and Taiji Suzuki. Dimension-free convergence rates for gradient Langevin dynamics in RKHS, COLT 2022. [Paper]

Adrien Vacher, Boris Muzellec, Alessandro Rudi, Francis Bach and François-Xavier Vialard. A Dimension-free Computational Upper Bound for Smooth Optimal Transport Estimation, COLT 2021. [Paper] [Code]

Hicham Janati, Boris Muzellec, Gabriel Peyré and Marco Cuturi. Entropic Optimal Transport between (Unbalanced) Gaussian Measures has a Closed Form, NeurIPS 2020 (oral). [Paper] [Video] [Code]

Boris Muzellec, Julie Josse, Claire Boyer and Marco Cuturi. Missing Data Imputation using Optimal Transport, ICML 2020. [Paper] [Video] [Code]

Boris Muzellec, Marco Cuturi. Subspace Detours: Building Transport Plans that are Optimal on Subspace Projections, NeurIPS 2019. [Paper] [Poster] [Slides] [Code]

Boris Muzellec, Marco Cuturi. Generalizing Point Embeddings using the Wasserstein Space of Elliptical Distributions, NeurIPS 2018. [Paper] [Poster] [Code]

Boris Muzellec, Richard Nock, Giorgio Patrini, Frank Nielsen. Tsallis Regularized Optimal Transport and Ecological Inference, AAAI 2017. [Paper] [Code]

Notes and technical reports

Boris Muzellec, Francis Bach and Alessandro Rudi. A Note on Optimizing Distributions using Kernel Mean Embeddings, arXiv preprint, 2021. [Paper] [Code]


Boris Muzellec, Maria Telenczuk, Vincent Cabeli and Mathieu Andreux. PyDESeq2: a python package for bulk RNA-seq differential expression analysis, python package, 2022. [Code]