back to listing index

carpedm20/variational-text-tensorflow

[web search]
Original source (github.com)
Tags: tensorflow
Clipped on: 2016-03-22

Skip to content
TensorFlow implementation of Neural Variational Inference for Text Processing
Python

README.md

Neural Variational Document Model

Tensorflow implementation of Neural Variational Inference for Text Processing.

Image (Asset 3/5) alt=

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

Usage

To train a model with Penn Tree Bank dataset:

normal$ python main.py --dataset ptb
normal

To test an existing model:

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

Results

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

Image (Asset 4/5) alt=

Image (Asset 5/5) alt=

Author

Taehoon Kim / @carpedm20