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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 2015Show all

5 papers · 1 filter

math.PR2015★ 14 cited

Existence, uniqueness, and regularity for stochastic evolution equations with irregular initial values

Adam Andersson, Arnulf Jentzen, Ryan Kurniawan

In this article we develop a framework for studying parabolic semilinear stochastic evolution equations (SEEs) with singularities in the initial condition and singularities at the…

math.PR2015★ 17 cited

Weak convergence rates for spatial spectral Galerkin approximations of semilinear stochastic wave equations with multiplicative noise

Ladislas Jacobe de Naurois, Arnulf Jentzen, Timo Welti

Stochastic wave equations appear in several models for evolutionary processes subject to random forces, such as the motion of a strand of DNA in a liquid or heat flow around a ring…

math.NA2015★ 30 cited

On stochastic differential equations with arbitrary slow convergence rates for strong approximation

Arnulf Jentzen, Thomas Müller-Gronbach, Larisa Yaroslavtseva

In the recent article [Hairer, M., Hutzenthaler, M., Jentzen, A., Loss of regularity for Kolmogorov equations, Ann. Probab. 43 (2015), no. 2, 468--527] it has been shown that there…

math.PR2015★ 26 cited

Strong convergence rates for an explicit numerical approximation method for stochastic evolution equations with non-globally Lipschitz continuous nonlinearities

Arnulf Jentzen, Primož Pušnik

In this article we propose a new, explicit and easily implementable numerical method for approximating a class of semilinear stochastic evolution equations with non-globally Lipsch…

math.PR2015★ 38 cited

Weak convergence rates for Euler-type approximations of semilinear stochastic evolution equations with nonlinear diffusion coefficients

Arnulf Jentzen, Ryan Kurniawan

Strong convergence rates for time-discrete numerical approximations of semilinear stochastic evolution equations (SEEs) with smooth and regular nonlinearities are well understood i…