This course provides a rigorous yet practical introduction to Bayesian methods for statistical inference, probabilistic modeling, knowledge representation, and decision-making under uncertainty.

We develop novel methods to make Bayesian inference more efficient, scalable, and practical. This includes work on variational methods, Monte Carlo algorithms, and techniques for handling complex ...