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AIMS OF THE SCHOOL
Stochastic differential equations (SDEs) are nowadays the core of many mathematical models of interest
in a large variety of applications, especially when the effects of uncertainty significantly affects the
underlying dynamics.
The complexity of SDE-based models requires to establish a comprehensive theory of numerical methods
to accurately and efficiently compute approximate solutions to SDEs.
This summer school is focused on providing an overall perspective on the numerical integration of SDEs.
The basic aspects of the problem will be clarified and several numerical methods will be presented.
The theoretical lectures will cover the basic notions of accuracy and stability, as well as numerical structure
preservation in SDEs. In addition, laboratory training sessions will be given every day, in order to make each
participant more aware of the computational problems.
The lectures will be organized in order to make the topics of the school as much self-contained as possible.
Prerequisites: basic numerics of ordinary differential equations; a favorite programming language for the
laboratory training sessions; basic aspects of stochastic processes.