Aaron Courville
Appointment
- Fellow
- Canada CIFAR AI Chair
- Learning in Machines & Brains
- Pan-Canadian AI Strategy
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About
Aaron Courville is a computer scientist whose current research focuses on the development of deep learning models and methods.
He is particularly interested in developing probabilistic models and novel inference methods. While he has mainly focused on applications to computer vision, he is also interested in other domains such as natural language processing, audio signal processing, speech understanding and just about any other artificial-intelligence-related task.
Awards
- Winning Team Member of the Transfer Learning Challenge, ICML Workshop, 2011
- Winning Team Member of the Unsupervised and Transfer Learning Challenge Phase II, NIPS, 2011
Relevant Publications
- Erhan, D. et al. "Why does unsupervised pre-training help deep learning?" J. Machine Learning Research 11 (2010): 625–60.
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