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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)

Dynamic Filter Networks NIPS 2016
Deep Exploration via Bootstrapped DQN NIPS 2016
Matching Networks for One Shot Learning NIPS 2016
Variational Inference in Mixed Probabilistic Submodular Models NIPS 2016
Review Networks for Caption Generation NIPS 2016
Distributed Flexible Nonlinear Tensor Factorization NIPS 2016
Multimodal Residual Learning for Visual QA NIPS 2016
Hierarchical Question-Image Co-Attention for Visual Question Answering NIPS 2016
Using Fast Weights to Attend to the Recent Past NIPS 2016
Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy NIPS 2016
Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale NIPS 2016
Deep Learning Models of the Retinal Response to Natural Scenes NIPS 2016
Learning Deep Parsimonious Representations NIPS 2016
Scalable Adaptive Stochastic Optimization Using Random Projections NIPS 2016
Memory-Efficient Backpropagation Through Time NIPS 2016
Relevant sparse codes with variational information bottleneck NIPS 2016
Learning What and Where to Draw NIPS 2016
Learning Sensor Multiplexing Design through Back-propagation NIPS 2016
Short-Dot: Computing Large Linear Transforms Distributedly Using Coded Short Dot Products NIPS 2016
SEBOOST - Boosting Stochastic Learning Using Subspace Optimization Techniques NIPS 2016
Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity NIPS 2016
Unsupervised Domain Adaptation with Residual Transfer Networks NIPS 2016
Conditional Image Generation with PixelCNN Decoders NIPS 2016
Tensor Switching Networks NIPS 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm NIPS 2016