About Erik von Schwerin Erik von Schwerin Research Scientist, Stochastic Numerics Research Group uncertainty quantification numerical analysis stochastic differential equations Stochastic Optimal Control Given a mathematical model of a system with uncertainties, a computational method of approximation of that model, and a specific Quantity of Interest (QoI) of the system, how can we, with as small computational effort as possible, approximate the QoI within a user-specified accuracy? Most of Erik von Schwerin's research relates in some way or another to this question. Projects Related Projects 2011 Adaptive Multi Level Monte Carlo (MLMC) Wed, Jun 1 2011 - Fri, Nov 1 2013 stochastic differential equations Stochastic differential equations (SDEs), both ordinary time-dependent equations and partial differential equations with random coefficients, are common mathematical tools to model natural processes with uncertainty.
Adaptive Multi Level Monte Carlo (MLMC) Wed, Jun 1 2011 - Fri, Nov 1 2013 stochastic differential equations Stochastic differential equations (SDEs), both ordinary time-dependent equations and partial differential equations with random coefficients, are common mathematical tools to model natural processes with uncertainty.
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