Likelihood-Based Generative Models

Variational Autoencoder

Introduced by Kingma et al. in Auto-Encoding Variational Bayes

A Variational Autoencoder is a type of likelihood-based generative model. It consists of an encoder, that takes in data $x$ as input and transforms this into a latent representation $z$, and a decoder, that takes a latent representation $z$ and returns a reconstruction $\hat{x}$. Inference is performed via variational inference to approximate the posterior of the model.

Source: Auto-Encoding Variational Bayes

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