Reading group on Deep Probability Models. UT Austin Fall 2017. Prof. James Scott.
A good review of variational inference from a Bayesian statistician's perspective is by Blei et. al.:
- Variational Inference: A Review for Statisticians. By David M. Blei, Alp Kucukelbir, and Jon D. McAuliffe.
- James's scribbles on VI
- R code for a simple Gaussian mixture model
Other topics:
2. Stochastic Variational Inference
3. Neural Networks & Back Propagation
4. Intro to Tensor Flow
5. Classical Autoencoders
6. Variational Autoencoders