We offer a wide range of graduate level general probability and stochastic processes courses which together form a comprehensive basis for advanced study in probability. These are augmented, yearly, by advanced special topic courses, as listed below.
Fall 2018
- Random Graphs - Yeo.
Spring 2018
- Random Matrices - Rosenthal.
Selection of courses from previous semesters
- Random interface models - Louidor.
- Hydrodynamic limits - Crawford.
- Universality of exit times for random walks - Wacthel.
- Gaussian Processes and Geometry - Adler
- Stochastic partial differential equations and measure-valued branching processes - Mytnik
- The discrete Gaussian free field and related topics - Louidor
- Gaussian Processes (and some geometry) - Adler.
- Long range dependence and heavy tails - Owada.
- The theory of random permutations and some connections to probabilistic number theory - Pinsky.
- Levy processes and local times of Markov processes - Kaspi.
- Markov Processes - Kaspi
- Spatial Stochastic Processes - Adler
- Large Scale Dynamics of Interacting Particles - Ioffe
- Directed Polymers and Random Geodesics - Ioffe
- Levy Processes - Mytnik
- Topological Methods in Electrical and Systems Engineering - Adler