Mathematics 797MR - ST-Info Theory&Model Reduction

In this course we discuss information theoretic methods for model reduction and model selection. Topics to be covered include: stochastic dynamics, coarse-graining and model reduction, relative entropy and mutual information, entropy and complex dynamics, information theory and statistics, maximum entropy methods, inequalities of information theory, information criteria for model selection and coarse-graining.

Open to Graduate students only. Please contact the instructor if you are interested in this course.