This project forked from liuzhian/vae-pytorch
This is the Pytorch implementation of variational auto-encoder, applying on MNIST dataset.
Currently, the following models are supported:
python train.pyThe code is self-explanatory, you can specify some customized options in train.py.
Here are some visualization results：
| Model | epoch 10 | epoch 20 | epoch 30 | epoch 40 | epoch 50 |
|---|---|---|---|---|---|
| VAE |  |
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| | | |
| Conv-VAE |  |
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| Model | epoch 10 | epoch 20 | epoch 30 | epoch 40 | epoch 50 |
|---|---|---|---|---|---|
| VAE |  |
 |
 |
| | | |
| Conv-VAE |  |
 |
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Donwload link:
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