Literature and slides

Literature (mandatory)

Literature (optional)

For the Probabilistic Programming part: For a better understanding of the link between the PGM/Bayesian network part and the probabilistic programming part:

Course slides (mandatory)

The lectures cover most of the above-mentioned literature, but some subjects will be discussed in more detail. You should be familiar with the additional details covered in the course slides:

Part 1 (syllabus chapters): Part 2 (RR04; Probabilistic programming): Part 3 (syllabus chapters): In case (some) slides are not yet available, you can check out last year's slides.

Video Lectures (optional)

🎦 For the 2020 online edition of the course the story that goes with the slides was recorded in videoclips. Each clip has its own subject and lasts about 10-30 minutes. These 'V-lectures' can be found on the UU video platform. Note that course slides have changed since 2020 and that the topic of probabilistic programming is not covered at all in the videos.

For a better understanding of the link between the PGM/Bayesian network part and the probabilistic programming part: see the material for the Introduction to Probabilistic Models (Nordic ProbAI 2024, Day 1)(when last checked, the videos were not yet uploaded, but slides are).

Further viewing: optional slides, videos etc

Further reading: optional textbooks

 J. Pearl
 Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
 Morgan Kaufmann Publishers, 1988.
 M. Studený
 On Probabilistic Conditional Independence Structures
 Information Science and Statistics, 2005. (requires UU IP-address)