Advanced Bayesian Learning, 7.5 credits

This is an advanced course in Bayesian statistics for PhD students in statistics, computer science, the engineering sciences and other related fields.
The course is divided into 3-5 contemporary topics in Bayesian analysis, and the choice of topics can vary from year to year depending on the research frontier.
The planned topics for the current year are (preliminary and subject to change):

1. Gaussian Processes with Applications
2. Bayesian Nonparametrics
3. (Stochastic) Variational Inference
4. Bayesian Model Inference

The course will run in April-May and the schedule will be travel-friendly. More information and schedule on the course page.

The prerequisite for this course is the introductory master level course Bayesian Learning (LiU) or Bayesian Statistics I (Stockholm University) or something equivalent.

Course Data
University: 
Stockholm
Type of schedule: 
Travel friendly schedule
Level: 
PhD
Credits (ECTS): 
7.50
Offered: 
2020:1