Multigrid (MG) solvers, typically increasing the computational time linearly with the grid size, are suitable for large-scale forward modeling problems. However, for electromagnetic (EM) problems as ...

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 ...

The paper describes the implementation details and validation results for an agglomeration multigrid procedure developed in the context of hybrid, unstructured grid solutions of aerodynamic flows. The ...

MGProx: A nonsmooth multigrid proximal gradient method with adaptive restriction for strongly convex optimization ...

In contrast to the standard algebraic multigrid, the Wavelet-based Algebraic Multigrid method relies more strongly on the smoothing method because the coarse spaces are chosen a priori. So, it is very ...

In this talk, I will first give an elementary introduction to models and algorithms from two different fields: (1) machine learning, including logistic regression and deep neural networks, and (2) ...

A picture of southwest crossroads in the central area of an ancient multigrid city found at the Erlitou relics site in Yanshi city, Henan province, marked by an archaeologists' team. [Photo/Xinhua ...

Multigrid methods: Fundamental algorithms, model problem analysis and applications -- Multi-grid convergence theory -- Guide to multigrid development -- The multi grid method and artificial viscosity ...

This paper proposes a new method for data assimilation of the surface radial current observed by High Frequency ground wave radar and optimization of the bottom friction coefficient. In this method, ...