most citedMultifidelity domain decomposition-based physics-informed neural networks and operators for time-dependent problems

3 citations · 3 across the 3 of their papers we have counts for

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math.NA2024★ 3 cited

Multifidelity domain decomposition-based physics-informed neural networks and operators for time-dependent problems

Alexander Heinlein, Amanda A. Howard, Damien Beecroft +1

Multiscale problems are challenging for neural network-based discretizations of differential equations, such as physics-informed neural networks (PINNs). This can be (partly) attri…

math.NA2021

An iterative solver for the HPS discretization applied to three dimensional Helmholtz problems

José Pablo Lucero Lorca, Natalie Beams, Damien Beecroft +1

This manuscript presents an efficient solver for the linear system that arises from the Hierarchical Poincaré-Steklov (HPS) discretization of three dimensional variable coefficient…