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Statistical Information Theory

  • 7.5 credits

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.

Further course information will appear soon on this page. Until then, information can be found on the department website.

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