Deep Learning Summer School, Montreal 2016
35 Lectures · Jul 31, 2016
About
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 2016 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.
Related categories
Uploaded videos:
Invited Talks
Machine Learning
Aug 23, 2016
·
52037 Views
Neural Networks
Aug 23, 2016
·
32378 Views
Introduction to Theano
Aug 23, 2016
·
7920 Views
Convolutional Neural Networks and Computer Vision
Aug 23, 2016
·
17015 Views
Learning to See
Aug 23, 2016
·
10016 Views
Introduction to Torch
Aug 23, 2016
·
5604 Views
Recurrent Neural Networks
Aug 23, 2016
·
42795 Views
Reasoning, Attention and Memory
Aug 23, 2016
·
13400 Views
Large Scale Deep Learning with TensorFlow
Aug 23, 2016
·
21687 Views
Deep Natural Language Understanding
Aug 23, 2016
·
20517 Views
Beyond Seq2Seq with Augmented RNNs
Aug 23, 2016
·
20758 Views
GPU programming for Deep Learning
Aug 23, 2016
·
5886 Views
Introduction to Reinforcement Learning
Aug 23, 2016
·
48641 Views
Deep Reinforcement Learning
Aug 23, 2016
·
38698 Views
Advanced Topics in RL
Aug 23, 2016
·
5126 Views
Advanced Topics in RL
Aug 23, 2016
·
4801 Views
Learning Deep Generative Models
Aug 23, 2016
·
14472 Views
Building Machines that Imagine and Reason: Principles and Applications of Deep G...
Aug 23, 2016
·
23370 Views
Beyond inspiration: Five lessons from biology on building intelligent machines
Aug 23, 2016
·
5786 Views
Theoretical neuroscience and deep learning theory
Aug 23, 2016
·
9502 Views
Contributed Talks
Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Ne...
Aug 23, 2016
·
4270 Views
Professor Forcing: A New Algorithm for Training Recurrent Networks
Aug 23, 2016
·
7242 Views
Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations
Aug 23, 2016
·
5893 Views
Deep multi-view representation learning of brain responses to natural stimuli
Aug 23, 2016
·
2890 Views
Learning to Communicate with Deep Multi-Agent Reinforcement Learning
Aug 23, 2016
·
7895 Views
Model-Based Relative Entropy Stochastic Search
Aug 23, 2016
·
2312 Views
Learning Nash Equilibrium for General-Sum Markov Games from Batch Dat
Aug 23, 2016
·
2030 Views
A Network-based End-to-End Trainable Task-oriented Dialogue System
Aug 23, 2016
·
4641 Views
Inference Learning
Aug 23, 2016
·
3039 Views
Variational Autoencoders with PixelCNN Decoders
Aug 23, 2016
·
5384 Views
An Infinite Restricted Boltzmann Machine
Aug 23, 2016
·
2707 Views
Deep siamese neural network for prediction of long-range interactions in chromat...
Aug 23, 2016
·
3016 Views
Beam Search Message Passing in Bidirectional RNNs: Applications to Fill-in-the-B...
Aug 23, 2016
·
3112 Views
Analyzing the Behavior of Deep Visual Question Answering Models
Aug 23, 2016
·
6126 Views
Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation
Aug 23, 2016
·
3059 Views