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Toward Spectral Deferred Correction Methods for Stochastic Differential Equations
The numerical solution of stochastic differential equations is computationally very demanding. Often it is of interest to evaluate certain moments, e.g., the expectation, by Monte Carlo sampling, thus requiring the computation of numerous realizations. The discretization error of the numerical schem
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