96 citations · 303 across the 55 of their papers we have counts for
5 papers · 1 filter
ELM-FBPINNs: An Efficient Multilevel Random Feature Method
Samuel Anderson, Victorita Dolean, Ben Moseley +1
Domain-decomposed variants of physics-informed neural networks (PINNs) such as finite basis PINNs (FBPINNs) mitigate some of PINNs' issues like slow convergence and spectral bias t…
Two-level deep domain decomposition method
Victorita Dolean, Serge Gratton, Alexander Heinlein +1
This study presents a two-level Deep Domain Decomposition Method (Deep-DDM) augmented with a coarse-level network for solving boundary value problems using physics-informed neural…
Schwarz preconditioner with -GenEO coarse space for the indefinite Helmholtz problem
Victorita Dolean, Mark Fry, Ivan G. Graham +1
GenEO (`Generalised Eigenvalue problems on the Overlap') is a method from the family of spectral coarse spaces that can efficiently rely on local eigensolves in order to build a ro…
Nonlinear Multilevel Solution Strategies for Diffusive Wave Flood Models in Perforated Domains
Miranda Boutilier, Konstantin Brenner, Victorita Dolean
This article investigates the numerical solution of the Diffusive Wave equation posed on domains containing a large number of polygonal perforations, motivated by urban flood model…
Can Symmetric Positive Definite (SPD) coarse spaces perform well for indefinite Helmholtz problems?
Victorita Dolean, Mark Fry, Matthias Langer
Wave propagation problems governed by the Helmholtz equation remain among the most challenging in scientific computing, due to their indefinite nature. Domain decomposition methods…