# pytorch-mnist-VAE

**Repository Path**: cheng_xiaofeng_1996/pytorch-mnist-VAE

## Basic Information

- **Project Name**: pytorch-mnist-VAE
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-03-29
- **Last Updated**: 2021-03-29

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## 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