1 citations · 1 across the 4 of their papers we have counts for
5 papers
A Locally Conservative Enriched Linearized Neural Network Approximation to Elliptic PDEs
Seungil Kim, Gwanghyun Jo, Young Ju Lee
This paper presents a locally conservative Enriched Linearized Neural Network (ENN) method for the Darcy flow model. A linearized shallow ReLU network, whose hidden-layer param…
Analysis of Error Propagation in Autoencoder-Based Reduced-Order Neural Ordinary Differential Equations
Jingyi Zhang, Gwanghyun Jo
Neural ODE reduced-order models often achieve comparable local prediction accuracy, yet their long-horizon extrapolation behavior can differ substantially. To analyze this discrepa…
Mixed virtual volume methods for elliptic problems
Gwanghyun Jo, Do Y. Kwak
We develop a class of mixed virtual volume methods for elliptic problems on polygonal/polyhedral grids. Unlike the mixed virtual element methods introduced in \cite{brezzi2014basic…
Locally conservative immersed finite element method for elliptic interface problems
Gwanghyun Jo, Do Young Kwak, Young Ju Lee
In this paper, we introduce the locally conservative enriched immersed finite element method (EIFEM) to tackle the elliptic problem with interface. The immersed finite element is u…
An IMPES scheme for a two-phase flow in heterogeneous porous media using a structured grid
Gwanghyun Jo, Do Y. Kwak
We develop a numerical scheme for a two-phase immiscible flow in heterogeneous porous media using a structured grid finite element method, which have been successfully used for the…