Mixture of Variational Autoencoders — a Fusion Between MoE and VAE

An unsupervised approach to digit classification and generation

The Variational Autoencoder (VAE) is a paragon for neural networks that try to learn the shape of the input space. Once trained, the model can be used to generate new samples from the input space.