About the event

This class will not be livestreamed or recorded.

David will discuss some of the issues related to inference in Machine Learning models, covering some of the landscape of techniques ranging from deterministic (for example, variational methods and perturbation theory) to stochastic approaches (for example, Monte Carlo). I will also discuss the optimisation methods and approaches to gradient computation. There will be more equations than pictures. This is an advanced session