adversarial autoencoder (AAE) with tensorflow for MNIST
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results
.gitignore
LICENSE
Model.py
README.md
batch_normalize.py
decoder.py
discriminator.py
encoder.py
main.py
make_fig.py
sampler.py
using_result.py
util.py

README.md

AAE

Adversarial Auto Encoder (AAE) with tensorflow for MNIST

usage

  • training
python main.py -d [MNIST csv file]
  • making figures after training
python using_result.py -d [MNIST csv file]

100 epoch results

AAE

Random sample from each Gaussian

0

0

1

1

2

2

walking from (0, 0) to (2, 0)

0to1

walking along with constant radius

const_r