Statistical Information Theory VT23

This course is taught in English.

The course aims at introducing the fundamental concepts in information theory, their relationship and their contemporary applications in statistics, machine learning, time series analysis, dynamical system, physics, etc. Topics that will be covered in the course include basic concepts of information theory, entropy rates of stochastic process, differential entropy, information flow & causal detection, statistical learning, rate distortion theory, information bottleneck, multivariate dependence and multi-information, etc. 

Course literature: 
A few chapters of the book, “Elements of Information Theory”, 2nd Ed. by Cover & Thomas, Wiley 2006, will be used to cover some fundamental concepts in information theory. Contemporary topics will be discussed in terms of journal papers.
Schedule

Please note that self-enrollment on the course page is not the same as course registration in Ladok.