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Tensorflow Implementation of GAN modeling for sequential data

Sequential Data GAN


This module is to generate sequential data with GAN implemented by LSTM.

The basic structure is followed ckmarkoh's git https://github.com/ckmarkoh/GAN-tensorflow

Used Data

For making sequential data, MNIST 0-3 data are used (0->1->2->3).

Modeling

Each modules, genrator and discreminator are designed with 2 layer LSTM and 1 layer Fully Connected Network. Generator is designed as one-to-many model, which get one random vector as input, and generates sequential images. Discriminator is designed as many-to-one model, which get sequential images, and decides that is real or fake ones.

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Results

Epoch 10 alt tag

Epoch 30 alt tag

Epoch 50 alt tag

Epoch 400 alt tag