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We propose a new probabilistic scheme which combines deep learning techniques with high order schemes for backward stochastic differential equations belonging to the class of Runge-Kutta methods to solve high-dimensional semi-linear parabolic partial differential equations.
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M. Hutzenthaler, A. Jentzen, T. Kruse, et al · 2019
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Cubature method to solve bsdes: Error expansion and complexity control
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Deep backward multistep schemes for nonlinear pdes and approximation error analysis
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Convergence of the deep bsde method for coupled fbsdes
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Deep backward schemes for high-dimensional nonlinear pdes
C. Huré, H. Pham, and X. Warin · 2020
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A numerical algorithm for a class of bsdes via the branching process
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Stratified regression monte-carlo scheme for semilinear pdes and bsdes with large scale parallelization on gpus
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Convergence of the deep bsde method for fbsdes with non-lipschitz coefficients
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