Welcome to STK4290/9290: Probabilistic Graphical Models!

The topic of the Spring 2023 version of STK4290/9290 is Probabilistic Graphical Models (PGMs). The course will give an introduction to the PGM framework, which aims at modelling a system of variables that interact with each other. The field of PGMs lie at the intersection of statistics and computer science, combining concepts from probability theory, graph algorithms and machine learning. We will look at the two most basic PGM representations: Bayesian Networks and Markov networks, and cover the main topics related to representation, inference, and learning.

As the main text book for the course, we will use: Koller, D. and Friedman, N. (2009). Probabilistic Graphical Models: Principles and Techniques. MIT Press. ISBN-13: 978-0262013192, ISBN-10: 0262013193.

Please send me an email if you have any questions about the course.