Xuechen Li

University of Toronto

Biography

I (almost) graduated from the University of Toronto with a specialist in CS and minors in Math and Stats. My research interests lie in the intersection of statistics, optimization, and machine learning. I am most interested in statistical foundations of modeling and inference. I am also interested in stochastic analysis and its connection to sampling and optimization.

During undergrad, I had the great fortune to work on research projects with Profs. David Duvenaud, Murat Erdogdu, and Roger Grosse. I am also excited about building better ML software. During summer 2018, I had the great fortune to intern at Google and work on the TensorFlow eager execution team.

Interests

Statistics
Optimization
Machine Learning

Education

BSc in Computer Science, 2019

University of Toronto

Publications

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