19 citations · 22 across the 4 of their papers we have counts for
3 papers · 1 filter
A robust and stable hybrid neural network/finite element method for 2D flows that generalizes to different geometries
Robert Jendersie, Nils Margenberg, Christian Lessig +1
The deep neural network multigrid solver (DNN-MG) combines a coarse-grid finite element simulation with a deep neural network that corrects the solution on finer grid levels, there…
DNN-MG: A Hybrid Neural Network/Finite Element Method with Applications to 3D Simulations of the Navier-Stokes Equations
Nils Margenberg, Robert Jendersie, Christian Lessig +1
We extend and analyze the deep neural network multigrid solver (DNN-MG) for the Navier-Stokes equations in three dimensions. The idea of the method is to augment a finite element s…
Deep neural networks for geometric multigrid methods
Nils Margenberg, Robert Jendersie, Thomas Richter +1
We investigate scaling and efficiency of the deep neural network multigrid method (DNN-MG). DNN-MG is a novel neural network-based technique for the simulation of the Navier-Stokes…