Training Latent Variable Models with Auto-encoding Variational Bayes: A Tutorial. (arXiv:2208.07818v1 [cs.LG])

Auto-encoding Variational Bayes (AEVB) is a powerful and general algorithm
for fitting latent variable models (a promising direction for unsupervised
learning), and is well-known for training the Variational Auto-Encoder (VAE).
In this tutorial, we focus on motivating AEVB from the classic Expectation
Maximization (EM) algorithm, as opposed to from deterministic auto-encoders.
Though natural and somewhat self-evident, the connection between EM and AEVB is
not emphasized in the recent deep learning literature, and we believe that
emphasizing this connection can improve …

arxiv bayes encoding lg training tutorial