I'm a PhD student at the University of Toronto, supervised by David Duvenaud. Previously, I had been a MSc student under Mark Schmidt, and an undergrad research assistant for Kevin Leyton-Brown.
Optimizing to generate quality research papers. Reward is sparse.
CV / Github / Google Scholar
Research
- Neural Networks with Cheap Differential Operators (SPOTLIGHT) Advances in Neural Information Processing Systems (NeurIPS). 2019 <polishing in progress>
- Residual Flows for Invertible Generative Modeling (SPOTLIGHT) Advances in Neural Information Processing Systems (NeurIPS). 2019 arxiv | bibtex | slides | poster | code
- Latent ODEs for Irregularly-Sampled Time Series Advances in Neural Information Processing Systems (NeurIPS). 2019 arxiv | code
- Invertible Residual Networks (LONG ORAL) International Conference on Machine Learning (ICML). 2019 arxiv | bibtex | code
-
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models
(ORAL)
(BEST STUDENT PAPER @ AABI 2018) International Conference on Learning Representations (ICLR). 2019 arxiv | bibtex | poster | code - Neural Ordinary Differential Equations (BEST PAPER AWARD) Advances in Neural Information Processing Systems (NeurIPS). 2018 arxiv | bibtex | slides | poster | code
- Isolating Sources of Disentanglement in Variational Autoencoders (ORAL) Advances in Neural Information Processing Systems (NeurIPS). 2018 arxiv | bibtex | slides | poster | code
- Learning Motion Predictors for Smart Wheelchair using Autoregressive Sparse Gaussian Process International Conference on Robotics and Automation (ICRA). 2018 arxiv | bibtex
- Deep kernel mean embeddings for generative modeling and feedforward style transfer MSc Thesis, University of British Columbia. 2017 pdf (18MB)
- Fast Patch-based Style Transfer of Arbitrary Style (ORAL) Workshop in Constructive Machine Learning, NIPS. 2016 arxiv | bibtex | slides | poster | code