See also my Google Scholar and Semantic Scholar pages.

Sampling from the Mean-Field Stationary Distribution
Yunbum Kook, Matthew S. Zhang, Sinho Chewi, Murat A. Erdogdu, M. Li.
Preprint 2024. [arXiv]

Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
Blake Bordelon, Lorenzo Noci, M. Li, Boris Hanin, Cengiz Pehlevan.
To appear at ICLR 2024. [arXiv]

Differential Equation Scaling Limits of Shaped and Unshaped Neural Networks
M. Li and Mihai Nica.
Preprint 2023. [arXiv]

The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit
Lorenzo Noci*, Chuning Li*, M. Li*, Bobby He, Thomas Hofmann, Chris Maddison, Daniel M. Roy.
NeurIPS 2023. [arXiv] [Proceeding]

Improved Discretization Analysis for Underdamped Langevin Monte Carlo
Matthew Zhang, Sinho Chewi, M. Li, Krishnakumar Balasubramanian, and Murat A. Erdogdu.
COLT 2023. [arXiv] [Proceeding]

Riemannian Langevin Algorithm for Solving Semidefinite Programs
M. Li and Murat A. Erdogdu.
Bernoulli 2023. [arXiv] [Journal]
Student Research Presentation Award at SSC 2021.

The Neural Covariance SDE: Shaped Infinite-Depth-and-Width Networks at Initialization
M. Li, Mihai Nica, and Daniel M. Roy.
NeurIPS 2022, Oral. [arXiv] [Proceeding] [Code] [DL Foundations at UMD (Video)] [OPTML++ at MIT (Video)]

Acceleration of Gossip Algorithms through the Euler-Poisson-Darboux Equation
Raphaël Berthier and M. Li (alphabetical).
IMA Journal of Applied Mathematics 2022. [arXiv] [Journal]

Analysis of Langevin Monte Carlo from Poincaré to Log-Sobolev
Sinho Chewi, Murat A. Erdogdu, M. Li, Ruoqi Shen, and Matthew Zhang (alphabetical).
COLT 2022 Extended Abstract. [arXiv] [Proceeding]

The Future is Log-Gaussian: ResNets and Their Infinite-Depth-and-Width Limit at Initialization
M. Li, Mihai Nica, and Daniel M. Roy.
NeurIPS 2021. [arXiv] [Proceeding] [Code]

Higher Order Generalization Error for First Order Discretization of Langevin Diffusion
M. Li and Maxime Gazeau.
Preprint 2021. [arXiv]

* Equal Contribution.