Neural Computation & Adaptive Perception Summer School

August 10-14, 2010
Toronto, Canada

This summer school is organized as part of the Neural Computation & Adaptive Perception research program of CIFAR.
It is hosted by the Machine Learning group at the Department of Computer Science, University of Toronto.


  • Bruno Olshausen, "Learning about vision: things we now know, things we still don't know, and things we don't know we don't know." [Slides ], "Intermediate-level vision" [Slides]

  • Siwei Lyu, "Natural Image Statistics" [Slides]

  • Urs Koster, "Estimating energy based models with Score Matching" [Slides]

  • Geoffrey Hinton, "Deep learning" [Slides]

  • Marc'Aurelio Ranzato, "Modeling Natural Images with Higher-Order Boltzmann Machines" [Slides]

  • Jascha Sohl-Dickstein, "Minimizing Probability Flow" [Slides]

  • Niko Troje, "Visual perception of human motion" [Slides]

  • David Fleet, "Human Motion Analysis" [Slides]

  • James Martens, "Deep Learning via Hessian-free optimization" [Slides]

  • Ilya Sutskever, "Training Recurrent Neural Networks to do cool stuff" [Slides]

  • Ryan Adams, "Monte Carlo Methods for Inference and Learning" [Slides]

    Talks (send your slides to