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06/03/2020
Space-time deep neural network approximations for high-dimensional partial differential equations
It is one of the most challenging issues in applied mathematics to appro...
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08/11/2019
Space-time error estimates for deep neural network approximations for differential equations
Over the last few years deep artificial neural networks (DNNs) have very...
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07/15/2019
Overcoming the curse of dimensionality in the numerical approximation of Allen-Cahn partial differential equations via truncated full-history recursive multilevel Picard approx
One of the most challenging problems in applied mathematics is the appro...
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09/07/2018
