jzilly/RecurrentHighwayNetworks
Implementation of Recurrent Highway Networks for language modeling across Tensorflow, Torch7, Theano, and Brainstorm frameworks.
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This repository provides implementations of Recurrent Highway Networks, a neural network architecture that extends LSTM with highway layers to enable deeper recurrent state transitions. The project enables training RHN models for word-level language modeling tasks on datasets like Penn Treebank. Implementations are provided for Tensorflow, Torch7, Theano, and Brainstorm, allowing researchers to compare performance across frameworks and reproduce benchmark results.
Frequently asked
- What is jzilly/RecurrentHighwayNetworks?
- Implementation of Recurrent Highway Networks for language modeling across Tensorflow, Torch7, Theano, and Brainstorm frameworks.
- Is RecurrentHighwayNetworks open source?
- Yes — jzilly/RecurrentHighwayNetworks is open source, released under the MIT license.
- What language is RecurrentHighwayNetworks written in?
- jzilly/RecurrentHighwayNetworks is primarily written in Python.
- How popular is RecurrentHighwayNetworks?
- jzilly/RecurrentHighwayNetworks has 402 stars on GitHub.
- Where can I find RecurrentHighwayNetworks?
- jzilly/RecurrentHighwayNetworks is on GitHub at https://github.com/jzilly/RecurrentHighwayNetworks.