This group is interested in techniques for approximate inference in complex probabilistic models.

Schedule

Bayesian deep learning

Done

Variational inference

Gradient estimation, baselines, and control variates

Discrete variables and relaxations

Normalising flows

Implicit models

Applications

Pool

Gradient Estimation

Support Material

Theses:

Tutorials and articles that read almost like tutorials:

Courses:

Gradient estimation:

Blogs: