Schedule & Material
The scheduled is preliminary and the order of lectures/practicals can (and will) change. The slides for the lectures and exercise sheets will be uploaded closer to the course start.
Lectures
Most of the scheduled time will consist of traditional lectures. Slides will be provided via this page, but note that the blackboard will be used quite extensively as well.
Practicals
Each day, a few hours of practical sessions are also scheduled. Assistants will be available to help you with the exercises and hand-in assignments during these sessions. A large share of the problems will be on implementation, so please bring your own laptop with a suitable language of your choice installed.
Monday (26/8)
Time | Room | Type | Topic(s) | Material |
---|---|---|---|---|
9.15-12.00 | Room IX![]() ![]() |
Lecture 1-3 | 1. Introduction and probabilistic modelling; 2. Probabilistic modelling of dynamical systems and the filtering problem; 3. Monte Carlo and importance sampling | Le1![]() ![]() ![]() |
Lunch on your own | ||||
13.15-15.00 | Room IX![]() ![]() |
Lecture 4-5 | 4. The bootstrap particle filter; 5. Convergence of bootstrap PF | Le4![]() ![]() |
15.15-17.00 | Room VIII![]() ![]() ![]() |
Practicals |
Tuesday (27/8)
Time | Room | Type | Topic(s) | Material |
---|---|---|---|---|
9.15-12.00 | Room IX![]() ![]() |
Lecture 6-8 | 6. Auxiliary variables and the auxiliary PF; 7. the fully adapted PF; 8. Path space view, path degeneracy and ESS | Le6![]() ![]() ![]() |
Lunch on your own | ||||
13.15-15.00 | Room VIII![]() ![]() ![]() |
Practicals | ||
15.15-17.00 | Room IX![]() ![]() |
Lecture 9-10 | 9. Parameter learning and likelihood estimation; 10. The particle filter as a likelihood estimator | Le9![]() ![]() |
Wednesday (28/8)
Time | Room | Type | Topic(s) | Material |
---|---|---|---|---|
10.15-12.00 | Room IV![]() ![]() |
Practicals | ||
Lunch on your own | ||||
13.15-15.00 | Room IV![]() ![]() |
Practicals |
Thursday (29/8)
Time | Room | Type | Topic(s) | Material |
---|---|---|---|---|
9.15-12.00 | Room IX![]() ![]() |
Lecture 11-13 | 11. Metropolis-Hastings; 12. Particle Metropolis-Hastings; 13. Gibbs sampling | Le11![]() ![]() ![]() |
Lunch on your own | ||||
13.15-15.00 | Room IX![]() ![]() |
Lecture 14-15 | 14. Particle Gibbs; 15. General SMC | Le14![]() ![]() |
15.15-17.00 | Room VIII![]() ![]() ![]() |
Practicals |
Friday (30/8)
Time | Room | Type | Topic(s) | Material |
---|---|---|---|---|
9.15-12.00 | Eva Netzeliussalen, Blåsens Hus![]() |
Lecture 16-18 | 16. SMC samplers; 17. SMC for probabilistic programming Jan Kudlicka![]() ![]() |
Le16![]() ![]() |
Lunch on your own |