Asymptotic theory examines the limiting behaviour of probabilistic and statistical quantities as the sample size or problem dimension grows without bound. Key pillars include the law of large numbers, ...

Research of the probability and statistics group includes particle systems, theoretical statistics, non-conventional random walks, random matrix theory, and random polynomials. Research interests also ...

This course builds a rigorous foundation of probability. Topics covered include: basic concepts of probability theory and statistics, counting, axioms of probability, independence, Bayes rule, ...

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Divergence measures quantify the dissimilarity between probability distributions and lie at the heart of modern information theory and statistical inference. Originating with the Kullback–Leibler ...

Introduction to probability theory and its applications. Axioms of probability, distributions, discrete and continuous random variables, conditional and joint distributions, correlation, limit laws, ...