I'm a fourth-year PhD student at Department of Computer Science, University of Toronto, supervised by Roger Grosse.
My research mainly focuses on Bayesian modelling, from both empirical and theoretical sides. I am also interested in reasoning with propositional and higher-order logic.
- Neural Networks as Inter-Domain Inducing Points AABI. 2021
- Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?[oral] AISTATS. 2021
- Fast-rate PAC-Bayes Generalization Bounds via Shifted Rademacher Processes NeurIPS. 2019
- Functional Variational Bayesian Neural Networks ICLR. 2019
- Aggregated Momentum: Stability Through Passive Damping ICLR. 2019
- Differentiable Compositional Kernel Learning for Gaussian Processes ICML. 2018
- Noisy Natural Gradient as Variational Inference ICML. 2018
- A Spectral Approach to Gradient Estimation for Implicit Distributions ICML. 2018
- Kernel implicit variational inference ICLR. 2018
- Learning structured weight uncertainty in bayesian neural networks AISTATS. 2017
- On the Spectral Efficiency of Massive MIMO Systems With Low-Resolution ADCs. IEEE Communications Letters. 2016