amitadate / S-LSTM-GAN-MNIST

This repository contains the source for the paper "S-LSTM-GAN: Shared recurrent neural networks with adversarial training"

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LSTM-GAN-MNIST

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Brief description:

Using the MNIST set to experiment with GANs using LSTM's

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Model

Following a generic generative adversarial network, the model consists two networks trained in parallel, and sharing weights. The pink portion of the model is the generator and the orange-brown portion is the discriminator. For purposes of clarity the image is split into quadrants here, but in other experiments the attempt was to split the image into pixels in an attempt to create a generator that could create digits pixel by pixel using long range memory. Up to now the best results have occurred with splitting the image into 16 sections, beyond that the model fails.

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Generator

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Discriminator

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Experiments

TIMESTEP MODEL

Variable Value
timesteps 4
lstm_layers_RNN_g 6
lstm_layers_RNN_d 2
hidden_size_RNN_g 600
hidden_size_RNN_d 400
lr 1e-4
iterations > 2.5e6

SAMPLES

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TIMESTEP MODEL

Variable Value
timesteps 16
lstm_layers_RNN_g 6
lstm_layers_RNN_d 2
hidden_size_RNN_g 600
hidden_size_RNN_d 400
lr 2e-4:GEN/1e-4:DISC
iterations > 5e5

SAMPLES

0 1 2 3 4 5 6 7 8 9
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About

This repository contains the source for the paper "S-LSTM-GAN: Shared recurrent neural networks with adversarial training"

License:MIT License


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