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UCL Tutorial on: Deep Belief Nets (An updated and extended version of my 2007 NIPS tutorial) Geoffrey Hinton Canadian Institute for Advanced Research & Department of Computer Science University of Toronto Schedule for the Tutorial • 2.00 – 3.30 Tutorial part 1 • 3.30 – 3.45 Questions • 3.45 - 4.15 Tea Break • 4.15 – 5.45 Tutorial part 2 • 5.45 – 6.00 Questions Some things you will learn in this tu

Information for prospective students, postdocs and visitors: I will not be taking any more students, postdocs or visitors. Basic papers on deep learning LeCun, Y., Bengio, Y. and Hinton, G. E. (2015) Deep Learning Nature, Vol. 521, pp 436-444. [pdf] Hinton, G. E., Osindero, S. and Teh, Y. (2006) A fast learning algorithm for deep belief nets. Neural Computation, 18, pp 1527-1554. [pdf] Movies of t

The setup for measuring the SHG is described in the supporting online material (22). We expect that the SHG strongly depends on the resonance that is excited. Obviously, the incident polariza- tion and the detuning of the laser wavelength from the resonance are of particular interest. One possibility for controlling the detuning is to change the laser wavelength for a given sample, which is diffic

Relevant literature Book chapter about the philosophy behind deep architecture model, motivating them in the context of Artificial Intelligence Scaling Learning Algorithms towards AI | pdf | Bengio, Y. and LeCun, Y. Book chapter in "Large-Scale Kernel Machines" Introducing Deep Belief Networks as generative models: A fast learning algorithm for deep belief nets | pdf ps.gz html | Hinton, G. E., Os

Training a deep autoencoder or a classifier on MNIST digits Code provided by Ruslan Salakhutdinov and Geoff Hinton Permission is granted for anyone to copy, use, modify, or distribute this program and accompanying programs and documents for any purpose, provided this copyright notice is retained and prominently displayed, along with a note saying that the original programs are available from our w

Information for prospective students, postdocs and visitors: I will not be taking any more students, postdocs or visitors. Basic papers on deep learning LeCun, Y., Bengio, Y. and Hinton, G. E. (2015) Deep Learning Nature, Vol. 521, pp 436-444. [pdf] Hinton, G. E., Osindero, S. and Teh, Y. (2006) A fast learning algorithm for deep belief nets. Neural Computation, 18, pp 1527-1554. [pdf] Movies of t