Graphical Models

2 hours of lectures per week.

Lecturer
Steffen L. Lauritzen, Aalborg University

Content
The course will give an introduction to graphical models based on directed acyclic graphs and their applications. Subjects covered include: Markov properties on directed graphs, Bayesian networks, local exact computation, graphical models for genetic analyses, the EM algorithm for Bayesian networks, Bayesian graphical models.

The course will be based on a combination of material from Lauritzen (1996), Cowell et al. (1999), lecture notes, selected journal articles, as well as graphical model software.

Assessment
Active participation in discussions, practical exercises and presentation.

Prerequisites
Basic understanding of probability and statistics is needed. It is an advantage to be familiar with elements of undirected graphical models, for example at the level of Lauritzen (1989).

Literature
S. L. Lauritzen, Lectures on Contingency Tables. 3rd ed. Department of Mathematics, Aalborg University. 1989. Electronic version 2002: http://www.math.auc.dk/~steffen/cont.pdf.
S. L. Lauritzen, Graphical Models, Clarendon Press, Oxford, 1996. [GM]
R. G. Cowell, A. P. Dawid, S. L. Lauritzen and D. J. Spiegelhalter, Probabilistic Networks and Expert Systems, Springer, New York, 1999. [PNS]

Software
HUGIN Lite 
WinBUGS 

Home page  

Course plan

Credits
10 ECTS.

Semester
Autumn 2003