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.

We reuse the data preparation script of the MNIST experiment

pip install -r requirements.txt
python ../mnist/data.py
python main.py