**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.

*Main course literature:*

[1] “Elements of Information Theory”, 2nd Ed. by Cover & Thomas, Wiley 2006

[2] “Neural Networks and Learning Machines”, 3rd Ed. by Haykin, Pearson Education Inc. 2009- Teacher: Chun-Biu Li
- Teacher: Joanna Tyrcha