4 citations · 8 across the 4 of their papers we have counts for
5 papers
Deep-Learning Solvers and Surrogates for Infinity and p-Laplace Problems
Tak Shing Au Yeung, Ka Chun Cheung, Hannah Potgieter +2
We investigate the use of neural network solvers for infinity and -Laplace problems, which are fundamental in nonlinear analysis and have practical applications. Our approach em…
Graph-Based Meshfree Multi-scale Coarse Space Approximation for Two-Level Schwarz Methods
Yucheng Liu, Tak Shing Au Yeung, Eric T. Chung +1
Efficient simulation of Darcy flow in highly heterogeneous porous media requires iterative solvers that remain robust under large permeability contrasts and mixed boundary conditio…
Learning Rays via Deep Neural Network in a Ray-based IPDG Method for High-Frequency Helmholtz Equations in Inhomogeneous Media
Tak Shing Au Yeung, Ka Chun Cheung, Eric T. Chung +2
We develop a deep learning approach to extract ray directions at discrete locations by analyzing highly oscillatory wave fields. A deep neural network is trained on a set of local…
A deep learning based nonlinear upscaling method for transport equations
Tak Shing Au Yeung, Eric T. Chung, Simon See
We will develop a nonlinear upscaling method for nonlinear transport equation. The proposed scheme gives a coarse scale equation for the cell average of the solution. In order to c…
Numerical inversion of 3D geodesic X-ray transform arising from traveltime tomography
Tak Shing Au Yeung, Eric T. Chung, Gunther Uhlmann
In this paper, we consider the inverse problem of determining an unknown function defined in three space dimensions from its geodesic X-ray transform. The standard X-ray transform…