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https://github.com/lyeoni/pytorch-mnist-vae

autoencoder deep-learning generative-model mnist pytorch vae

Last synced: 9 days ago
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Host: GitHub
URL: https://github.com/lyeoni/pytorch-mnist-vae
Owner: lyeoni
Created: 2018-10-23T05:21:47.000Z (about 6 years ago)
Default Branch: master
Last Pushed: 2018-10-25T05:47:13.000Z (about 6 years ago)
Last Synced: 2023-09-28T11:29:16.091Z (about 1 year ago)
Topics: autoencoder, deep-learning, generative-model, mnist, pytorch, vae
Language: Jupyter Notebook
Size: 10.8 MB
Stars: 94
Watchers: 4
Forks: 44
Open Issues: 1
Metadata Files:
- Readme: README.md

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README

# pytorch-mnist-VAE
Variational AutoEncoder on the MNIST data set using the PyTorch

## Dependencies
- PyTorch
- torchvision
- numpy

## Results
Generated samples from 2-D latent variable with random numbers from a normal distribution with mean 0 and variance 1

![alt text](https://github.com/lyeoni/pytorch-mnist-VAE/blob/master/samples/sample_.png)

## Reference
1. Auto-Encoding Variational Bayes. Diederik P Kingma, Max Welling (paper):
https://arxiv.org/abs/1312.6114
2. 오토인코더의 모든 것 (slides):
https://www.slideshare.net/NaverEngineering/ss-96581209
3. Basic VAE Example (github):
https://github.com/pytorch/examples/tree/master/vae
4. hwalsuklee/tensorflow-mnist-VAE (github):
https://github.com/hwalsuklee/tensorflow-mnist-VAE