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Academic Freedom.
Computational Power.
Massive Datasets.
Curiosity-driven research dedicated to achieving
state-of-the-art in machine learning and artificial intelligence.

Publications

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On the Effectiveness of Low Frequency Perturbations
Authors: Y. Sharma, G. W. Ding , M. Brubaker

Private Q-Learning with Functional Noise in Continuous Spaces
Authors: B. Wang , N. Hegde

Skynet: A Top Deep RL Agent in the Inaugural Pommerman Team Competition
Authors: C. Gao, P. Hernandez-Leal , B. Kartal , M. Taylor

Learning a Deep ConvNet for Multi-label Classification with Partial Labels
Authors: T. Durand , N. Mehrasa , G. Mori

A Variational Auto-Encoder Model for Stochastic Point Process
Authors: N. Mehrasa , A. Jyothi , T. Durand , J. He, Prof. L. Sigal , G. Mori

On the Sensitivity of Adversarial Robustness to Input Data Distributions
Authors: G. Weiguang Ding , K. Lui , T. Jin, L. Wang, R. Huang
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Updates

Intelligibility is a key component to trust in machine learning
Blog

How Vancouver hit its AI stride
Press

Six ways to confront bias in AI - and how Canada can lead the way
Blog

Vancouver, Edmonton, and Waterloo research centres draw on unique local design
Blog

AdverTorch: A toolbox for adversarial robustness research
Blog

Applying Differential Privacy to Deep Reinforcement Learning
Blog