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Variational Autoencoder on Common-MNIST-Dataset Using PyTorch

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README.md		README.md
model.py		model.py
train.py		train.py

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Variational Autoencoder on MNIST

VAE paper: Auto-Encoding Variational Bayes

Results

All plots obtained after 10 epochs of training. Hyperparameters accordning to default settings in the code; not tuned.

z ~ q(z|x)

The modeled latent distribution after 10 epochs and 35 samples per digit.

p(x|z)

Randomly sampled z, and their output.

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Variational Autoencoder on Common-MNIST-Dataset Using PyTorch

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Python 100.0%