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- W3200422139 abstract "In this paper, we derive error estimates of the backward Euler-Maruyama method applied to multi-valued stochastic differential equations. An important example of such an equation is a stochastic gradient flow whose associated potential is not continuously differentiable, but assumed to be convex. We show that the backward Euler-Maruyama method is well-defined and convergent of order at least $1/4$ with respect to the root-mean-square norm. Our error analysis relies on techniques for deterministic problems developed in [Nochetto, Savar'e, and Verdi, Comm. Pure Appl. Math., 2000]. We verify that our setting applies to an overdamped Langevin equation with a discontinuous gradient and to a spatially semi-discrete approximation of the stochastic $p$-Laplace equation." @default.
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- W3200422139 date "2021-09-14" @default.
- W3200422139 modified "2023-10-16" @default.
- W3200422139 title "Error estimates of the backward Euler–Maruyama method for multi-valued stochastic differential equations" @default.
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- W3200422139 doi "https://doi.org/10.1007/s10543-021-00893-w" @default.
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