Skip to content
CIFAR header logo
fr
menu_mobile_logo_alt
  • About
    • Our Story
    • Awards
    • Partnerships
    • President’s Message
    • Publications & Reports
    • Careers
    • Equity, Diversity & Inclusion
  • News
  • People
    • Fellows & Advisors
    • CIFAR Azrieli Global Scholars
    • Canada CIFAR AI Chairs
    • AI Strategy Leadership
    • Solution Network Members
    • Staff Directory
    • Leadership
  • Programs
    • Research Programs
    • Knowledge Mobilization
    • Pan-Canadian AI Strategy
    • Next Generation Initiatives
    • Global Call for Ideas
    • Action on Covid-19
  • Events
    • Public Events
    • Invitation-only Meetings
  • Support Us
  • fr
  • Home
  • Bio

Follow Us

Aaron

Aaron Courville

Appointment

  • Fellow
  • Canada CIFAR AI Chair
  • Learning in Machines & Brains
  • Pan-Canadian AI Strategy

Connect

Université de Montréal

Google Scholar

About

Aaron Courville is a Canada CIFAR AI Chair at Mila, a CIFAR fellow of the Learning in Machines and Brains program, and an associate professor in the Department of Computer Science and Operations Research (DIRO) at Université de Montréal.

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

  • Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., & Courville, A. (2017). Improved training of wasserstein gans.

  • Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT press.

  • Xu, K., Ba, J., Kiros, R., Cho, K., Courville, A., Salakhudinov, R., … & Bengio, Y. (2015). Show, attend and tell: Neural image caption generation with visual attention. In International conference on machine learning (pp. 2048-2057). PMLR.

  • Bengio, Y., Courville, A., & Vincent, P. (2013). Representation learning: A review and new perspectives. IEEE transactions on pattern analysis and machine intelligence, 35(8), 1798-1828.

  • Erhan, D., Courville, A., Bengio, Y., & Vincent, P. (2010). Why does unsupervised pre-training help deep learning?. In Proceedings of the thirteenth international conference on artificial intelligence and statistics (pp. 201-208). JMLR Workshop and Conference Proceedings.

Institution

  • Mila
  • Université de Montréal

Department

Department of Computer Science and Operations Research (DIRO)

Education

  • PhD (Computer Science), Carnegie Mellon University
  • MASc, University of Toronto
  • BASc (Engineering Science), University of Toronto

Country

  • Canada

Support Us

CIFAR is a registered charitable organization supported by the governments of Canada, Alberta and Quebec, as well as foundations, individuals, corporations and Canadian and international partner organizations.

Donate Now
CIFAR header logo

Subscribe

Stay up to date on news & ideas from CIFAR.

MaRS Centre, West Tower
661 University Ave., Suite 505
Toronto, ON M5G 1M1 Canada

Contact Us
Media
Careers
Accessibility Policies
Supporters
Financial Reports
Subscribe

  • © Copyright 2022 CIFAR. All Rights Reserved.
  • Charitable Registration Number: 11921 9251 RR0001
  • Terms of Use
  • Privacy
  • Sitemap
This website stores cookies on your computer. These cookies are used to collect information about how you interact with our website and allow us to remember you. We use this information in order to improve and customize your browsing experience and for analytics and metrics about our visitors both on this website and other media. To find out more about the cookies we use, see our Privacy Policy.
Accept Learn more