In this paper, we propose a systematic approach for accelerating finite element-type
methods by machine learning for the numerical solution of partial differential equations …

In applications such as free-space optical communication, a signal is often recovered after
propagation through a turbulent medium. In this setting, it is common to assume that limited …

With nested grids or related approaches, it is known that numerical artifacts can be
generated at the interface of mesh refinement. Most of the existing methods of minimizing …

Radiative transfer is important for many science and engineering applications, and
numerical simulations of radiative transfer can be challenging. For instance, the radiation …

In the past decade,(artificial) neural networks and machine learning tools have surfaced as
game changing technologies across numerous fields, solving an array of challenging …