Department of Information Technology

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, University main building 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 Le2 Le3
Lunch on your own
13.15-15.00 Room IX, University main building Lecture 4-5 4. The bootstrap particle filter; 5. Convergence of bootstrap PF Le4 Le5
15.15-17.00 Room VIII and Room XI, University main building Practicals

Tuesday (27/8)

Time Room Type Topic(s) Material
9.15-12.00 Room IX, University main building Lecture 6-8 6. Auxiliary variables and the auxiliary PF; 7. the fully adapted PF; 8. Path space view, path degeneracy and ESS Le6 Le7 Le8
Lunch on your own
13.15-15.00 Room VIII and Room XI, University main building Practicals
15.15-17.00 Room IX, University main building Lecture 9-10 9. Parameter learning and likelihood estimation; 10. The particle filter as a likelihood estimator Le9 Le10

Wednesday (28/8)

Time Room Type Topic(s) Material
10.15-12.00 Room IV, University main building Practicals
Lunch on your own
13.15-15.00 Room IV, University main building Practicals

Thursday (29/8)

Time Room Type Topic(s) Material
9.15-12.00 Room IX, University main building Lecture 11-13 11. Metropolis-Hastings; 12. Particle Metropolis-Hastings; 13. Gibbs sampling Le11 Le12 Le13 Code le13
Lunch on your own
13.15-15.00 Room IX, University main building Lecture 14-15 14. Particle Gibbs; 15. General SMC Le14 Le15
15.15-17.00 Room VIII and Room XI, University main building 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; 18. Guest lecture by Fredrik Ronquist. Le16 Le17
Lunch on your own
Updated  2019-09-02 11:32:10 by Johan Alenlöv.