Roger is an Assistant Professor of Computer Science at the University of Toronto, focusing on machine learning. Previously, He was a postdoc at Toronto, after having received a Ph.D. at MIT, studying under Bill Freeman and Josh Tenenbaum. Before that, Roger did his undergraduate degree in symbolic systems and MS in computer science at Stanford University. Roger is a co-creator of Metacademy, a web site which uses a dependency graph of concepts to help you formulate personalized learning plans for machine learning and related topics.
Faculty Member
Assistant Professor, Department Computer Science, Faculty of Arts & Science, University of Toronto
Canada CIFAR Artificial Intelligence Chair
Sloan Research Fellow
Highlights
- Connaught New Researcher Award
- Canada Research Chair in Probabilistic Inference and Deep Learning
Publications
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches
International Conference on Learning Representations (ICLR) 2018
Understanding Short-Horizon Bias in Stochastic Meta-Optimization
International Conference on Learning Representations (ICLR) 2018
Scalable trust-region method for deep reinforcement learning using kronecker-factored approximation
Advances in Neural Information Processing Systems (NIPS) 2017
The reversible residual network: Backpropagation without storing activations
Advances in Neural Information Processing Systems (NIPS) 2017
Lime: Learning inductive bias for primitives of mathematical reasoning
2021
Differentiable annealed importance sampling and the perils of gradient noise
2021
On Monotonic Linear Interpolation of Neural Network Parameters
2021
REFACTOR: Learning to Extract Theorems from Proofs
2021
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds
2021