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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Recurrent & convolutional neural network modules
| Date | Stars |
|---|---|
| 2026-07-31 | 356 |
| 2026-08-01 | 356 |
| 2026-08-02 | 356 |
| 2026-08-06 | 356 |
Today
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growth rate 0.00%/day
### Latest updates Check [code/rationale](/code/rationale) for the project of learning rationales for neural prediction: <p align="center"> <img height =140 src="code/rationale/figures/example.png"> <img width=350 src="code/rationale/figures/model_framework.png"> [Adam Yala](https://github.com/yala/) has implemented a **Pytorch** version of the rationale project! Check it out at: https://github.com/yala/text_nn </p> ------- #### About this repo This repo contains Theano implementations of popular neural network components and optimization methods. Source code of the following papers are also available: [1] [Molding CNNs for text: non-linear, non-consecutive convolutions](http://arxiv.org/abs/1508.04112). EMNLP 2015 [2] [Semi-supervised Question Retrieval with Gated Convolutions](http://arxiv.org/abs/1512.05726). NAACL 2016 [3] [Rationalizing Neural Predictions](https://people.csail.mit.edu/taolei/papers/emnlp16_rationale.pdf). EMNLP 2016 #### Features - Basic modules including feedforward layer, dropout, word embedding, RNN, LSTM, GRU and CNN - Optimization methods including SGD, AdaGrad, AdaDelta and Adam - Advanced modules from recent papers such as attention and gated convolution. - Transparent to use GPU ------- #### Projects ###### 1. Neural question retrieval for community-based QA The directories [code/qa](/code/qa) and [code/pt](/code/pt) contain the implementation of the model described in paper [[2]](http://arxiv.org/abs/1512.05726). Datasets and and pre-trained word vectors are available at [here](https://github.com/taolei87/askubuntu). ###### 2. Sentiment analysis / document classification The directory [code/sentiment](/code/sentiment) contains the implementation of the model described in paper [[1]](http://arxiv.org/abs/1508.04112). Datasets and and pre-trained word vectors are available at [here](https://github.com/taolei87/text_convnet). ###### 3. Rationalizing neural predictions The directory [code/rationale](/code/rationale) contains the implementation of the model described in paper [[3]](https://people.csail.mit.edu/taolei/papers/emnlp16_rationale.pdf). ------- #### Dependencies [Theano](http://deeplearning.net/software/theano/) >= 0.7, Python >= 2.7, Numpy -------
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:4875954d0416748f, llm:Description: 'Recurrent & convolutional neural network modules' (repository provides neural network modules combining RNNs and CNNs). Language: Python.
matched fp:4875954d0416748f, llm:Description: 'Recurrent & convolutional neural network modules' (repository provides neural network modules combining RNNs and CNNs). Language: Python.
matched fp:4875954d0416748f, llm:Description: 'Recurrent & convolutional neural network modules' (repository provides neural network modules combining RNNs and CNNs). Language: Python.