Special topics in probability and statistics offered according to student demand and faculty availability.

Stochastic evolutions are widespread in probability, economics, statistics, and theoretical physics, and are commonly used to model various real-life phenomena. This class focuses on non-stationary evolutions in which the variance grows in time. We discuss both classical approaches, based on approximations with Brownian motions and Ito integrals, and modern high-dimensional settings, where objects of random matrix theory become relevant. Prerequisite: rigorous foundations of probability theory. The rest will be defined and explained.

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