I am a Research Fellow at Mathematics Department of National University of Singapore (NUS), working with Soh Yong Sheng. Before that, I did a short postdoc at Telecom Paristech, working with Florence d’Alché, Gabriel Peyré and Remi Flamary on the applications of optimal transport to machine learning. My current research interest is on optimal transport and diffusion models, with a focus on methodological/theoretical side.
I obtained my PhD in Proba-Stat team of Département de Mathématiques d’Orsay and INRIA Parietal team, working with problems in high-dimension statistics. I was very fortunate to be advised by Sylvain Arlot and Bertrand Thirion. I spent a fair amount of time during my PhD for the developments of open-source softwares. Checkout Nilearn, hidimstat, and Benchopt for the open-source projects that I have been developing/contributing to.
tuanbinhs [AT] gmail.com, or
binhnt [AT] nus.edu.sg(see also my Google Scholar. *: equal contributions)
Chen, JY.*, BN* , Soh, YS. Semidefinite Relaxations of the Gromov-Wasserstein Distance. NeuRIPS 2024. [paper] [code] [reviews] – A preliminary version was presented at the Optimal Transport and Machine Learning workshop at NeuRIPS 2023.
Nguyen, NB., BN, Nguyen, TH., Nguyen, VA. Generative Conditional Distributions by Neural (Entropic) Optimal Transport, ICML 2024. [paper] [code]
Nguyen, NB., BN, Nguyen, VA. Bellman Optimal Step-size Straightening of Flow-Matching Models, ICLR 2024. [paper & reviews] [code]
Dao, Q., Phung, H., BN, & Tran, A. Flow Matching in Latent Space. arXiv 2023. [paper] [code]
BN, Thirion, B., & Arlot, S. A Conditional Randomization Test for Sparse Logistic Regression in High-Dimension. NeuRIPS 2022. [paper] [code] [reviews]
Moreau, T. et al. Benchopt: Reproducible, efficient and collaborative optimization benchmarks. NeuRIPS 2022. [paper] [code] [reviews]
J.-A. Chevalier, BN, B. Thirion J. Salmon, Spatially relaxed inference on high-dimensional linear models. Statistics & Computing 32, 83 (2022). [paper]
J.-A. Chevalier, BN, J. Salmon, G. Varoquaux, B. Thirion, Decoding with confidence: Statistical control on decoder maps. In NeuroImage, Volume 234, 2021, 117921, ISSN 1053-8119. [paper]
BN, J.-A. Chevalier, B.Thirion, & S. Arlot, Aggregation of Multiple Knockoffs. In Proceedings of the 37th International Conference on Machine Learning (ICML); PMLR 119:7283-7293, 2020. [paper] [code]
BN, J.-A Chevalier, & B. Thirion, ECKO: Ensemble of Clustered Knockoffs for Robust Multivariate Inference on fMRI Data. In International Conference on Information Processing in Medical Imaging (pp. 454-466). Springer, Cham., 2019 [paper]