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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.

May 6, 2019

On the Sensitivity of Adversarial Robustness to Input Data Distributions

Authors: G. Weiguang Ding , K. Lui , X. Jin, L. Wang, R. Huang

Jan. 28, 2019

Using Monte Carlo Tree Search as a Demonstrator within Asynchronous Deep RL

Authors: B. Kartal , P. Hernandez-Leal , M. E. Taylor

Dec. 7, 2018

On Learning Wire-Length Efficient Neural Networks

Authors: C. Blake , L. Wang, G. Castiglione , C. Srinivasa , M. Brubaker

Dec. 7, 2018

Few-Shot Self Reminder to Overcome Catastrophic Forgetting

Authors: J. Wen, Y. Cao , R. Huang

Dec. 7, 2018

Compositional Hard Negatives for Visual Semantic Embeddings via an Adversary

Authors: *A. J. Bose, *H. Ling, Y. Cao

* Denotes equal contribution

Sept. 20, 2018

Skill Reuse in Partially Observable Multiagent Environments

Authors: P. Hernandez-Leal , B. Kartal , M. Taylor

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Everything old is new again: Tackling classical problems with modern techniques at AAAI 2019

Blog

Kathryn Hume joins Borealis AI leadership team

Blog

How to Set Up an AI R&D Lab

Press

The Pommerman team competition or: How we learned to stop worrying and love the battle

Blog

Northern Frontier: In conversation with Abhishek Gupta

Video

Doors open for Borealis AI's metro-inspired Montreal research centre

Blog