Skip to content
master
Go to file
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 

README.md

Minimal Variational Auto-Encoder

This is a minimal implementation of an Variational Auto-Encoder in Tensorflow applied to MNIST.

Some example generated numbers:

VAE results

How to run

Simply clone the directory and run the file vae_mnist.py. Results will be displayed in real time, while full training takes a few minutes.

Implementation details

The implementation follows Auto-Encoding Variational Bayes. Both the generator and discriminator uses 3 convolutional layers with 5x5 convolutions, with obvious room for improvements.

About

A minimal implementation of an Variational Auto-Encoder

Topics

Resources

License

Releases

No releases published

Packages

No packages published

Languages

You can’t perform that action at this time.