vae_conv

Convolutional variational autoencoder in PyTorch

Basic VAE Example

This is an improved implementation of the paper Stochastic Gradient VB and the Variational Auto-Encoder by Kingma and Welling. It uses ReLUs and the adam optimizer, instead of sigmoids and adagrad. These changes make the network converge much faster.

pip install -r requirements.txt
python main.py