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Statistical Information Theory

Information theory is at the intersection of mathematics, statistics, computer science and several other fields, with applications in many areas.

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, multivariate dependence and multi-information.