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Deep learning approximations for non-local nonlinear PDEs with Neumann
  boundary conditions

Deep learning approximations for non-local nonlinear PDEs with Neumann boundary conditions

7 May 2022
V. Boussange
S. Becker
Arnulf Jentzen
Benno Kuckuck
Loïc Pellissier
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Papers citing "Deep learning approximations for non-local nonlinear PDEs with Neumann boundary conditions"

3 / 3 papers shown
Title
Full error analysis of the random deep splitting method for nonlinear parabolic PDEs and PIDEs
Full error analysis of the random deep splitting method for nonlinear parabolic PDEs and PIDEs
Ariel Neufeld
Philipp Schmocker
Sizhou Wu
45
7
0
08 May 2024
Deep Neural Network Algorithms for Parabolic PIDEs and Applications in
  Insurance Mathematics
Deep Neural Network Algorithms for Parabolic PIDEs and Applications in Insurance Mathematics
R. Frey
Verena Köck
42
16
0
23 Sep 2021
An overview on deep learning-based approximation methods for partial
  differential equations
An overview on deep learning-based approximation methods for partial differential equations
C. Beck
Martin Hutzenthaler
Arnulf Jentzen
Benno Kuckuck
30
146
0
22 Dec 2020
1