When should I use a variational autoencoder as opposed to an autoencoder?

• VAE give prior on the distribution of latent variable, if you want precise control over your latent representations and what you would like them to represent, then choose VAE. Sometimes, precise modeling can capture better representations as in [2].

VAE is a framework that was proposed as a scalable way to do variational EM (or variational inference in general) on large datasets. Although it has an AE like structure, it serves a much larger purpose.