Seungchan Ko

According to our database, Seungchan Ko authored at least 7 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

VS-PINN: A Fast and efficient training of physics-informed neural networks using variable-scaling methods for solving PDEs with stiff behavior.

Seungchan Ko, Sang Hyeon Park

CoRR, 2024

Error analysis for finite element operator learning methods for solving parametric second-order elliptic PDEs.

Youngjoon Hong, Seungchan Ko, Jae Yong Lee

CoRR, 2024

2023

A novel approach for wafer defect pattern classification based on topological data analysis.

Seungchan Ko, Dowan Koo

Expert Syst. Appl., November, 2023

Finite Element Operator Network for Solving Parametric PDEs.

Jae Yong Lee, Seungchan Ko, Youngjoon Hong

CoRR, 2023

2022

Convergence analysis of unsupervised Legendre-Galerkin neural networks for linear second-order elliptic PDEs.

Seungchan Ko, Seok-Bae Yun, Youngjoon Hong

CoRR, 2022

Quasi-Monte Carlo finite element approximation of the Navier-Stokes equations with initial data modeled by log-normal random fields.

Seungchan Ko, Guanglian Li, Yi Yu

CoRR, 2022

2019

Finite element approximation of steady flows of generalized Newtonian fluids with concentration-dependent power-law index.

Seungchan Ko, Endre Süli

Math. Comput., 2019