A multigrid inversion approach that uses variable resolutions of both the data space and the image space is proposed. Since the computational complexity of inverse problems typically increases with a ...

Cascadic multigrid methods represent a class of iterative solvers that have been developed to efficiently tackle the large-scale linear systems arising from the discretisation of partial ...

Algebraic multigrid (AMG) methods have emerged as a crucial tool for efficiently solving large, sparse linear systems, particularly those arising in complex scientific and engineering simulations.

In this paper, we introduce a fast method for 3-D modeling of EM data, based on a modified version of quasilinear approximation, which uses a multigrid approach. This method significantly speeds up ...