# Latent Diffusion Series: Variational Autoencoder (VAE)

In the Latent Diffusion Series of blog posts, I'm going through all components needed to train a latent diffusion model to generate random digits from the MNIST dataset. In the second post, we will build and train a variational autoencoder to generate MNIST digits. The latent variables of these models are defined to be normally distributed, something that will later enable our diffusion model operate in the latent space.