https://github.com/lyeoni/pytorch-mnist-vae
https://github.com/lyeoni/pytorch-mnist-vae
autoencoder deep-learning generative-model mnist pytorch vae
Last synced: 3 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 (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2018-10-25T05:47:13.000Z (almost 7 years ago)
- Last Synced: 2025-03-22T14:02:12.341Z (7 months ago)
- Topics: autoencoder, deep-learning, generative-model, mnist, pytorch, vae
- Language: Jupyter Notebook
- Size: 10.8 MB
- Stars: 111
- Watchers: 3
- Forks: 48
- Open Issues: 1
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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
## 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