1 citations · 2 across the 2 of their papers we have counts for
2 papers
math.NA2022★ 1 cited
Semi-analytic PINN methods for singularly perturbed boundary value problems
Gung-Min Gie, Youngjoon Hong, Chang-Yeol Jung
We propose a new semi-analytic physics informed neural network (PINN) to solve singularly perturbed boundary value problems. The PINN is a scientific machine learning framework tha…
math.AP2016★ 1 cited
The aggregation equation with Newtonian potential
Elaine Cozzi, Gung-Min Gie, James P Kelliher
The viscous and inviscid aggregation equation with Newtonian potential models a number of different physical systems, and has close analogs in 2D incompressible fluid mechanics. We…