variational-text-tensorflow

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variational-text-tensorflow

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TensorFlow implementation of Neural Variational Inference for Text Processing

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최종 버전 다운로드 (.zip)

- 2016-03-20-final-hist.png
- 2016-03-20-final-scalar.png
- model.png
- training-2016-03-20.png
- training-2016-03-21.png
- - test.txt
  - train.txt
  - valid.txt
- - test.txt
  - train.txt
  - valid.txt
- __init__.py
- base.py
- nasm.py
- nvdm.py
.gitignore
batch_loader.py
LICENSE
main.py
reader.py
README.md
toy_generator.py
utils.py

// repository documentation

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Neural Variational Document Model
=================================

Tensorflow implementation of [Neural Variational Inference for Text Processing](http://arxiv.org/abs/1511.06038).

![model_demo](https://raw.githubusercontent.com/carpedm20/variational-text-tensorflow/master/assets/model.png)

This implementation contains:

1. Neural Variational Document Model
    - Variational inference framework for generative model of text
    - Combines a stochastic document representation with a bag-of-words generative model 
2. Neural Answer Selection Model (in progress)
    - Variational inference framework for conditional generative model of text
    - Combines a LSTM embeddings with an attention mechanism to extract the semantics between question and answer

Prerequisites
-------------

- Python 2.7 or Python 3.3+
- [NLTK](http://www.nltk.org/)
- [TensorFlow](https://www.tensorflow.org/)

Usage
-----

To train a model with Penn Tree Bank dataset:

$ python main.py --dataset ptb

To test an existing model:

$ python main.py --dataset ptb --forward_only True

Results
-------

Training details of NVDM. The best result can be achieved by onehost updates, not alternative updates.

![scalar](https://raw.githubusercontent.com/carpedm20/variational-text-tensorflow/master/assets/2016-03-20-final-scalar.png)

![histogram](https://raw.githubusercontent.com/carpedm20/variational-text-tensorflow/master/assets/2016-03-20-final-hist.png)

Author
------

Taehoon Kim / [@carpedm20](http://carpedm20.github.io/)

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