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Deep Learning

66,648 papers (25 classified directly here)

Subtopics

Learning Types (28,663) Architectures (27,448) Models (16,617) Techniques (8,241) Optimization & Theory (6,829) Application Areas (46)

Papers per year

2
65
428
6150
10854
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Papers (including subtopics)

Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning ICML 2016
Generative Adversarial Text to Image Synthesis ICML 2016
Deep Structured Energy Based Models for Anomaly Detection ICML 2016
Unitary Evolution Recurrent Neural Networks ICML 2016
Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks ICML 2016
Learning to Generate with Memory ICML 2016
Learning End-to-end Video Classification with Rank-Pooling ICML 2016
Train faster, generalize better: Stability of stochastic gradient descent ICML 2016
Factored Temporal Sigmoid Belief Networks for Sequence Learning ICML 2016
Strongly-Typed Recurrent Neural Networks ICML 2016
Texture Networks: Feed-forward Synthesis of Textures and Stylized Images ICML 2016
Auxiliary Deep Generative Models ICML 2016
One-Shot Generalization in Deep Generative Models ICML 2016
Autoencoding beyond pixels using a learned similarity metric ICML 2016
From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification ICML 2016
Fast Parameter Inference in Nonlinear Dynamical Systems using Iterative Gradient Matching ICML 2016
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors ICML 2016
Learning Granger Causality for Hawkes Processes ICML 2016
Neural Variational Inference for Text Processing ICML 2016
Pixel Recurrent Neural Networks ICML 2016
Gaussian quadrature for matrix inverse forms with applications ICML 2016
Meta-Learning with Memory-Augmented Neural Networks ICML 2016
Exploiting Cyclic Symmetry in Convolutional Neural Networks ICML 2016
Associative Long Short-Term Memory ICML 2016
Learning Convolutional Neural Networks for Graphs ICML 2016