Compete to Compute
Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets
Invariant backpropagation: how to train a transformation-invariant neural network
Memory Networks
Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks
DRAW: A Recurrent Neural Network For Image Generation
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
A New Framework to Probe and Learn Neural Networks
Text Understanding from Scratch
Do Deep Nets Really Need to be Deep?
Effective Use of Word Order for Text Categorization with Convolutional Neural Networks
Why does Deep Learning work? - A perspective from Group Theory
FitNets: Hints for Thin Deep Nets
Exploring Invariances in Deep Convolutional Neural Networks Using Synthetic Images
Deep Fried Convnets
Deep Speech: Scaling up end-to-end speech recognition
Recurrent Models of Visual Attention
Teaching Deep Convolutional Neural Networks to Play Go
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
An exact mapping between the Variational Renormalization Group and Deep Learning
Advances in Optimizing Recurrent Networks
Very Deep Convolutional Networks for Large-Scale Visual Recognition
k-Sparse Autoencoders
A Clockwork RNN
Random feedback weights support learning in deep neural networks
Learning to Execute
Neural Turing Machines
