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Deep Learning Summer School 2015 - Montreal   

Deep Learning Summer School, Montreal 2015

Deep neural networks that learn to represent data in multiple layers of increasing abstraction have dramatically improved the state-of-the-art for speech recognition, object recognition, object detection, predicting the activity of drug molecules, and many other tasks. Deep learning discovers intricate structure in large datasets by building distributed representations, either via supervised, unsupervised or reinforcement learning.

The Deep Learning Summer School 2015 is aimed at graduate students and industrial engineers and researchers who already have some basic knowledge of machine learning (and possibly but not necessarily of deep learning) and wish to learn more about this rapidly growing field of research.
Categories
votesvotesvotesvotesvotes [syn]  83109 views, 1:29:11  
flagIntroduction to Machine LearningIntroduction to Machine Learning
Pascal Vincent Pascal Vincent
comments20 comments 
votesvotesvotesvotesvotes [syn]  87490 views, 1:32:18  
flagDeep Learning:Theoretical MotivationsDeep Learning:Theoretical Motivations
Yoshua Bengio Yoshua Bengio
comments68 comments 
votesvotesvotesvotesvotes [syn]  22577 views, 1:36:48  
flagMultilayer Neural NetworksMultilayer Neural Networks
Léon Bottou Léon Bottou
votesvotesvotesvotesvotes [syn]  24184 views, 1:25:11  
flagTraining Deep Neural NetworksTraining Deep Neural Networks
Hugo Larochelle Hugo Larochelle
comments1 comment 
votesvotesvotesvotesvotes [syn]  10689 views, 1:31:05  
flagMultilayer Neural NetworksMultilayer Neural Networks
Léon Bottou Léon Bottou
comments2 comments 
votesvotesvotesvotesvotes [syn]  14038 views, 1:24:18  
flagDeep Learning for Distribution EstimationDeep Learning for Distribution Estimation
Hugo Larochelle Hugo Larochelle
votesvotesvotesvotesvotes [syn]  11516 views, 1:22:17  
flagUndirected Graphical ModelsUndirected Graphical Models
Aaron Courville Aaron Courville
comments4 comments 
votesvotesvotesvotesvotes [syn]  10401 views, 1:28:35  
flagStacks of Restricted Boltzmann MachinesStacks of Restricted Boltzmann Machines
Honglak Lee Honglak Lee
votesvotesvotesvotesvotes [syn]  13344 views, 1:33:31  
flagOn manifolds and autoencodersOn manifolds and autoencoders
Pascal Vincent Pascal Vincent
votesvotesvotesvotesvotes [syn]  7668 views, 1:28:51  
flagVisual features: From Fourier to GaborVisual features: From Fourier to Gabor
Roland Memisevic Roland Memisevic
votesvotesvotesvotesvotes [syn]  16809 views, 1:31:59  
flagConvolutional NetworksConvolutional Networks
Honglak Lee Honglak Lee
[syn]  7117 views, 1:14:33  
flagLearning to CompareLearning to Compare
Graham Taylor Graham Taylor
votesvotesvotesvotesvotes [syn]  19265 views, 1:28:23  
flagNLP and Deep Learning 1: Human Language & Word Vectors NLP and Deep Learning 1: Human Language & Word Vectors
Christopher Manning Christopher Manning
comments5 comments 
votesvotesvotesvotesvotes [syn]  6246 views, 1:25:47  
flagSeeing People with Deep LearningSeeing People with Deep Learning
Graham Taylor Graham Taylor
votesvotesvotesvotesvotes [syn]  8900 views, 1:25:18  
flagNLP and Deep Learning 2: Compositional Deep Learning NLP and Deep Learning 2: Compositional Deep Learning
Christopher Manning Christopher Manning
comments1 comment 
votesvotesvotesvotesvotes [syn]  32706 views, 1:26:10  
flagDeep Learning Deep Learning
Ruslan Salakhutdinov Ruslan Salakhutdinov
comments11 comments 
votesvotesvotesvotesvotes [syn]  9267 views, 1:27:20  
flagSpeech Recognition and Deep LearningSpeech Recognition and Deep Learning
Adam Coates Adam Coates
votesvotesvotesvotesvotes [syn]  12035 views, 1:14:34  
flagDeep Learning 2Deep Learning 2
Ruslan Salakhutdinov Ruslan Salakhutdinov
votesvotesvotesvotesvotes [syn]  22608 views, 1:24:38  
flagTutorial on Neural Network Optimization ProblemsTutorial on Neural Network Optimization Problems
Ian Goodfellow Ian Goodfellow
comments1 comment 
votesvotesvotesvotesvotes [syn]  6967 views, 1:25:37  
flagDeep Learning (hopefully faster) Deep Learning (hopefully faster)
Adam Coates Adam Coates
votesvotesvotesvotesvotes [syn]  10778 views, 1:29:54  
flagAdversarial ExamplesAdversarial Examples
Ian Goodfellow Ian Goodfellow
votesvotesvotesvotesvotes [syn]  6910 views, 1:25:30  
flagFrom Language Modelling to Machine TranslationFrom Language Modelling to Machine Translation
Phil Blunsom Phil Blunsom
votesvotesvotesvotesvotes [syn]  11762 views, 1:22:00  
flagDeep NLP Recurrent Neural NetworksDeep NLP Recurrent Neural Networks
Richard Socher Richard Socher
comments1 comment 
votesvotesvotesvotesvotes [syn]  7179 views, 1:22:49  
flagMemory, Reading, and ComprehensionMemory, Reading, and Comprehension
Phil Blunsom Phil Blunsom
votesvotesvotesvotesvotes [syn]  9778 views, 1:20:28  
flagDeep NLP Applications and Dynamic Memory NetworksDeep NLP Applications and Dynamic Memory Networks
Richard Socher Richard Socher
comments1 comment 
votesvotesvotesvotesvotes [syn]  7513 views, 1:30:26  
flagSmooth, Finite, and Convex Optimization Deep Learning Summer SchoolSmooth, Finite, and Convex Optimization Deep Learning Summer School
Mark Schmidt Mark Schmidt
votesvotesvotesvotesvotes [syn]  4287 views, 1:27:06  
flagVisual features IIVisual features II
Roland Memisevic Roland Memisevic
votesvotesvotesvotesvotes [syn]  7405 views, 1:32:19  
flagNon Smooth, Non Finite, and Non Convex OptimizationNon Smooth, Non Finite, and Non Convex Optimization
Mark Schmidt Mark Schmidt
votesvotesvotesvotesvotes [syn]  18303 views, 1:32:51  
flagVariational Autoencoder and ExtensionsVariational Autoencoder and Extensions
Aaron Courville Aaron Courville
comments2 comments 
votesvotesvotesvotesvotes [syn]  20079 views, 1:26:48  
flagDeep Generative ModelsDeep Generative Models
Yoshua Bengio Yoshua Bengio

Reviews and comments:

Comment1 Gustavo Botelho de Souza, March 9, 2016 at 3:10 p.m.:

Hello.

Are you preparing an edition of the Deep Learning Summer School in 2016?

Best regards.

Gustavo

Comment2 Narges Feshang, May 4, 2016 at 4:57 p.m.:

Deep Learning for medicine

Comment3 Harrell, November 23, 2019 at 8:08 p.m.:

Nice blog with lots of information!

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