Aidan Li

Research Interests

  • Causal inference
  • Probabilistic machine learning
  • Graph neural networks
  • Cognitive science

Biography

I am a fourth year Computer Science and Statistics student at the University of Toronto. My previous work includes two industry internships working with graph neural networks, and research on Markov chain Monte Carlo efficiency supervised by Prof. Jeffrey Rosenthal at the University of Toronto. I will be interning at the LIONS lab at EPFL for 3 months under the Excellence Research Internship Program.

High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization

Y. Chen; F. Liu; T. Suzuki; V. Cevher 

2024. 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024.

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Generalization of Scaled Deep ResNets in the Mean-Field Regime

Y. Chen; F. Liu; Y. Lu; G. Chrysos; V. Cevher 

2024. 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024.

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Contact

e-mail: Aidan Li

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