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https://github.com/lagleki/recurrent_neural_network_variants_examples

Implmentation of recurrent neural network and its' variants.
https://github.com/lagleki/recurrent_neural_network_variants_examples

Last synced: 15 days ago
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Implmentation of recurrent neural network and its' variants.

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## Implementation of RNN and its' variants

Currently Implemented Papers:
* [Quasi-Recurrent Neural Networks](https://arxiv.org/pdf/1611.01576.pdf) James Bradbury, Stephen Merity, Caiming Xiong, Richard Socher
* [Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks](https://arxiv.org/abs/1708.06834)
* [Training RNNs as fast as CNNs](https://arxiv.org/pdf/1709.02755)[code](https://github.com/taolei87/sru)
* [Kronecker Highway RNN](https://arxiv.org/pdf/1705.10142.pdf)
* [Delta RNN](https://arxiv.org/pdf/1703.08864.pdf)
* [Highway Networks](https://arxiv.org/abs/1505.00387)
* [Recurrent Highway Networks](http://arxiv.org/abs/1607.03474)
* [Multiplicative Integration Within RNNs](https://arxiv.org/abs/1606.06630)
* [Recurrent Dropout](http://arxiv.org/pdf/1603.05118v1.pdf)
* [Layer Normalization](http://arxiv.org/abs/1607.06450)
* [Layer Normalization & Multiplicative Integration](http://arxiv.org/abs/1607.06450)
* [LSTM With Multiple Memory Arrays](https://arxiv.org/abs/1607.03085)
* [Minimal Gated Unit RNN](http://arxiv.org/abs/1603.09420)
* [Residual Connections Within Stacked RNNs](https://arxiv.org/abs/1609.08144)
* [GRU Mutants](http://www.jmlr.org/proceedings/papers/v37/jozefowicz15.pdf)
* [Weight Tying](https://arxiv.org/abs/1608.05859)