'Rbm j j j' presentation slideshows

2007 NIPS Tutorial on: Deep Belief Nets

2007 NIPS Tutorial on: Deep Belief Nets. Geoffrey Hinton Canadian Institute for Advanced Research & Department of Computer Science University of Toronto. Some things you will learn in this tutorial.

1.15k views • 100 slides

2007 NIPS Tutorial on: Deep Belief Nets

2007 NIPS Tutorial on: Deep Belief Nets. Geoffrey Hinton Canadian Institute for Advanced Research & Department of Computer Science University of Toronto. Some things you will learn in this tutorial.

1.15k views • 100 slides

An overview of deep learning

An overview of deep learning. Geoffrey Hinton University of Toronto & Canadian Institute for Advanced Research & G o o g l e. A brief history of deep neural networks. How to recognize patterns: First convert raw input into feature activations.

1.06k views • 69 slides

The next generation of neural networks

1. The next generation of neural networks. Geoffrey Hinton Canadian Institute for Advanced Research & University of Toronto. 2. The main aim of neural networks. People are much better than computers at recognizing patterns. How do they do it?

1.11k views • 47 slides

Highlights of Hinton's Contrastive Divergence Pre-NIPS Workshop

Highlights of Hinton's Contrastive Divergence Pre-NIPS Workshop. Yoshua Bengio & Pascal Lamblin USING SLIDES FROM Geoffrey Hinton, Sue Becker & Yann Le Cun. Overview. Motivations for learning deep unsupervised models Reminder: Boltzmann Machine & energy-based models

567 views • 42 slides

CSC321 2007 Lecture 23: Sigmoid Belief Nets and the wake-sleep algorithm

384 views • 19 slides