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05/07/2022
Deep learning approximations for non-local nonlinear PDEs with Neumann boundary conditions
Nonlinear partial differential equations (PDEs) are used to model dynami...
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12/29/2021
Deep neural network approximation theory for high-dimensional functions
The purpose of this article is to develop machinery to study the capacit...
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10/15/2021
Strong L^p-error analysis of nonlinear Monte Carlo approximations for high-dimensional semilinear partial differential equations
Full-history recursive multilevel Picard (MLP) approximation schemes hav...
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12/22/2020
An overview on deep learning-based approximation methods for partial differential equations
It is one of the most challenging problems in applied mathematics to app...
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09/30/2019
