Department of Computational Perception
Department of
Computational Perception
Johannes Kepler Universität Linz

Home  –  Mission  –  Teaching  –  People  –  Research  –  Media  –  Awards  –  Impressum


344.036, VO, 2 hrs. (3 ECTS), WS 2017/18

Univ.-Prof. Dr. Gerhard Widmer

This class will be taught in English.

TIME: Tuesday, 09:15 - 10:45
START: Tuesday, Oct. 3, 2017
PLACE: HS 14 (TNF Tower, ground floor)


Here is a little set of Introduction & Motivation Slides ...

Goals and Contents of this Class:

This course is a gentle introduction to one of the most important and central classes of methods in present-day Artificial Intelligence. It will introduce students to the basic concepts of Probabilistic Graphical Models as representations of uncertain knowledge in complex domains. All three aspects related to such models will be covered: model semantics, inference, and learning. In particular, the following topics will be covered (in more or less detail): It is strongly recommended to take this VO together with the "Practical Excercises in Probabilistic Models" (UE, 1h) in the same semester. There, the students will perform practical experiments with some of the methods taught in the VO.

Teaching materials:

Pdf versions of the Powerpoint slides used in the lecture will be made available via KUSSS (weekly).

Recommended reading (will not be needed if the lectures are attended on a regular basis):

Koller, Daphne and Friedman, Nir (2009).
Probabilistic Graphical Models: Principles and Techniques. Cambridge, MA: MIT Press.

Russell, Stuart J. and Norvig, Peter (2003).
Artificial Intelligence: A Modern Approach. Englewood Cliffs, NJ: Prentice Hall.

Questions, suggestions, complaints, etc. to:

Gerhard Widmer
Tel. 2468-4701
gerhard dot widmer at jku dot at

last edited by gw on Aug 16, 2017