Xuechen Li

University of Toronto

Biography

I graduated from the University of Toronto with a specialist in computer science and minors in mathematics and statistics. My research interests lie in the intersection of statistics, optimization, and machine learning. I am most interested in statistical foundations of modeling and inference. Recently, I am also interested in theoretical aspects of sampling and optimization and how insights thereof help explain global convergence of neural networks. During undergrad, I had the great fortune to work on research projects with profs. David Duvenaud, Murat Erdogdu, and Roger Grosse.

Interests

Statistics
Optimization
Machine Learning

Education

BSc in Computer Science, 2019

University of Toronto

Research

Xuechen Li, Denny Wu, Lester Mackey, Murat A. Erdogdu. Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond. 2019.

Preprint

George Barmpalias, Neng Huang, Andrew Lewis-Pye, Angsheng Li, Xuechen Li, Yicheng Pan, Tim Roughgarden. The idemetric property: when most distances are (almost) the same. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2019.

PDF

Ricky T. Q. Chen, Xuechen Li, Roger Grosse, David Duvenaud. Isolating Sources of Disentanglement in Variational Autoencoders. Advances in Neural Information Processing Systems (NeurIPS), 2018.

Preprint

Chris Cremer, Xuechen Li, David Duvenaud. Inference Suboptimality in Variational Autoencoders. International Conference on Machine Learning (ICML), 2018.

Preprint

Contact

lxuechen@cs.toronto.edu