Zobrazeno 1 - 10
of 230
pro vyhledávání: '"Dolean, Victorita"'
Physics Informed Neural Networks (PINNs) offer several advantages when compared to traditional numerical methods for solving PDEs, such as being a mesh-free approach and being easily extendable to solving inverse problems. One promising approach for
Externí odkaz:
http://arxiv.org/abs/2409.01949
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 networks (PINNs). The addition of the coarse level network improves sc
Externí odkaz:
http://arxiv.org/abs/2408.12198
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 robust parallel domain decomposition preconditioner for elliptic PDEs. W
Externí odkaz:
http://arxiv.org/abs/2406.06283
This article focuses on the numerical solution of the Diffusive Wave equation posed in a domain containing a large number of polygonal perforations. These numerous perforations represent structures in urban areas, and this problem is used to model ur
Externí odkaz:
http://arxiv.org/abs/2406.06189
The purpose of this work is to improve the estimates for the $\Delta$-GenEO method from the paper "Overlapping Schwarz methods with GenEO coarse spaces for indefinite and nonself-adjoint problems" by N. Bootland, V. Dolean, I. G Graham, C. Ma, R. Sch
Externí odkaz:
http://arxiv.org/abs/2403.18378
In this paper we design, analyse and test domain decomposition methods for linear systems of equations arising from conforming finite element discretisations of positive Maxwell-type equations, namely for $\mathbf{H}(\mathbf{curl})$ problems. It is w
Externí odkaz:
http://arxiv.org/abs/2311.18783
Autor:
Borzooei, Sahar, Tournier, Pierre-Henri, Dolean, Victorita, Pichot, Christian, Joachimowicz, Nadine, Roussel, Helene, Migliaccio, Claire
A portable imaging system for the on-site detection of shoulder injury is necessary to identify its extent and avoid its development to severe condition. Here, firstly a microwave tomography system is introduced using state-of-the-art numerical model
Externí odkaz:
http://arxiv.org/abs/2311.05322
For the Poisson equation posed in a domain containing a large number of polygonal perforations, we propose a low-dimensional coarse approximation space based on a coarse polygonal partitioning of the domain. Similarly to other multiscale numerical me
Externí odkaz:
http://arxiv.org/abs/2310.15669
This article discusses the uncertainty quantification (UQ) for time-independent linear and nonlinear partial differential equation (PDE)-based systems with random model parameters carried out using sampling-free intrusive stochastic Galerkin method l
Externí odkaz:
http://arxiv.org/abs/2310.14649
Physics-informed neural networks (PINNs) are a powerful approach for solving problems involving differential equations, yet they often struggle to solve problems with high frequency and/or multi-scale solutions. Finite basis physics-informed neural n
Externí odkaz:
http://arxiv.org/abs/2306.05486