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20092026
most citedSolving high-dimensional partial differential equations using deep learning

1.8k citations · 7.5k across the 146 of their papers we have counts for

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Showing 2016Show all

9 papers · 1 filter

math.PR2016★ 12 cited

On the mild Itô formula in Banach spaces

Sonja Cox, Arnulf Jentzen, Ryan Kurniawan +1

The mild Ito formula proposed in Theorem 1 in [Da Prato, G., Jentzen, A., \& Röckner, M., A mild Ito formula for SPDEs, arXiv:1009.3526 (2012), To appear in the Trans.\ Amer.\ Math…

math.PR2016★ 7 cited

Weak convergence rates for numerical approximations of stochastic partial differential equations with nonlinear diffusion coefficients in UMD Banach spaces

Mario Hefter, Arnulf Jentzen, Ryan Kurniawan

Strong convergence rates for numerical approximations of semilinear stochastic partial differential equations (SPDEs) with smooth and regular nonlinearities are well understood in…

math.AP2016★ 14 cited

Regularity properties for solutions of infinite dimensional Kolmogorov equations in Hilbert spaces

Adam Andersson, Mario Hefter, Arnulf Jentzen +1

In this article we establish regularity properties for solutions of infinite dimensional Kolmogorov equations. We prove that if the nonlinear drift coefficients, the nonlinear diff…

math.PR2016★ 2 cited

On the differentiability of solutions of stochastic evolution equations with respect to their initial values

Adam Andersson, Arnulf Jentzen, Ryan Kurniawan +1

In this article we study the differentiability of solutions of parabolic semilinear stochastic evolution equations (SEEs) with respect to their initial values. We prove that if the…

math.PR2016★ 15 cited

Exponential moments for numerical approximations of stochastic partial differential equations

Arnulf Jentzen, Primož Pušnik

Stochastic partial differential equations (SPDEs) have become a crucial ingredient in a number of models from economics and the natural sciences. Many SPDEs that appear in such app…

math.NA2016★ 69 cited

Multilevel Picard iterations for solving smooth semilinear parabolic heat equations

Weinan E, Martin Hutzenthaler, Arnulf Jentzen +1

We introduce a new family of numerical algorithms for approximating solutions of general high-dimensional semilinear parabolic partial differential equations at single space-time p…