awesome-very-deep-learning
github.com/daviddao/awesome-very-deep-learning ↗♾A curated list of papers and code about very deep neural networks
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Neural Ordinary Differential EquationsValue Iteration NetworksDensely Connected Convolutional NetworksDeep Residual LearningHighway NetworksVery Deep Learning Theory
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Deep Residual Learning
Very Deep Learning Theory
- A Simple Way to Initialize Recurrent Networks of Rectified Linear UnitsPapers
- Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual CortexPapers
- Demystifying ResNetPapers
- Highway and Residual Networks learn Unrolled Iterative EstimationPapers
- Identity Matters in Deep LearningPapers
- Residual Networks are Exponential Ensembles of Relatively Shallow NetworksPapers
Neural Ordinary Differential Equations
- Augmented Neural ODEs (2019)Papers
- Autograd ImplementationImplementations
- Neural Ordinary Differential Equations (2018)Papers
Highway Networks
Densely Connected Convolutional Networks
- Caffe ImplementationImplementations
- Chainer ImplementationImplementations
- Chainer ImplementationImplementations
- Densely Connected Convolutional Networks (2016)Papers
- Keras ImplementationImplementations
- Keras ImplementationImplementations
Value Iteration Networks
Showing a sample of 60 resources. View the full list on GitHub →