Schedule
The exercises and lectures are on Wednesdays in T2 (CS-House). The exercises are at 14:15-15:00 and the lectures are 15:15-17:00. Note that the first lecture is on January 8th and there is no exercise session on that day. Due to the Covid-19 situation, the lectures on 18.3., 25.3., and 1.4. have been replaced with videos and quizzes.
The lecture slides, virtual whiteboard notes, and lecture videos are also linked below. If the links don't work for some reason, everything can also be found in Materials section.
- 8.1. Arrangements of Course in Spring 2020 and Overview of Bayesian modeling of time-varying systems (no exercise session before this lecture)
- 15.1. From linear regression to Kalman filter and beyond -- Notes from iPad 15.1.2020
- 22.1. Bayesian optimal filtering equations and the Kalman filter -- Notes from iPad 22.1.2020
- 29.1. Extended Kalman filter and statistical linearization -- Notes from iPad 29.1.2020
- 5.2. Unscented Kalman filter, Gaussian Filter, GHKF and CKF -- Notes from iPad 5.2.2020
- 12.2. Information on project work
- 19.2. (no lecture, no exercise session)
- 26.2. Particle filtering -- Notes from iPad 26.2.2020
- 26.2. Individual project work starts (= project topic selection deadline)
- 4.3. Rao-Blackwellized particle filtering -- Notes from iPad 4.3.2020
- 11.3. Bayesian optimal smoother, Rauch-Tung-Striebel smoothing -- Notes from iPad 11.3.2020
- 18.3. Gaussian and particle smoothers -- Lecture 9 Video - Part 1 (Quiz 9.1) / Lecture 9 Video - Part 2 (Quiz 9.2) / Lecture 9 Video - Part 3 (Quiz 9.3)
- 25.3. Bayesian estimation of parameters in state space models -- Lecture 10 Video - Part 1 (Quiz 10.1) / Lecture 10 Video - Part 2 (Quiz 10.2) / Lecture 10 Video - Part 3 (Quiz 10.3)
- 1.4. Recap of the course topics
- 8.4. Examination -- this is organized as an online exam in mycourses
- 12.4. Project work deadline