Seungchan Ko - RankMe

17 papers Journal 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Sobolev Approximation of Deep ReLU Networks in Log-Barron Space. CoRR Changhoon Song, Seungchan Ko, Youngjoon Hong
2026	J	`jnl`	Sparse FEONet: A Low-Cost, Memory-Efficient Operator Network via Finite-Element Local Sparsity for Parametric PDEs. CoRR Seungchan Ko, Jiyeon Kim, Dongwook Shin
2026	J	`jnl`	Task-aware evolution in physics-informed neural networks: Application to Saint-Venant torsion problems. Eng. Appl. Artif. Intell. Su Yeong Jo, Sanghyeon Park, Jeesuk Shin, Jongcheon Park, Hosung Kim, Seungchan Ko, Sangseung Lee, Joongoo Jeon
2025	J	`jnl`	Data-free Asymptotics-Informed Operator Networks for Singularly Perturbed PDEs. CoRR Jinsil Lee, Youngjoon Hong, Seungchan Ko, Jae Yong Lee
2025	J	`jnl`	Engineering application of physics-informed neural networks for Saint-Venant torsion. CoRR Su Yeong Jo, Sanghyeon Park, Seungchan Ko, Jongcheon Park, Hosung Kim, Sangseung Lee, Joongoo Jeon
2025	J	`jnl`	Error analysis for a fully-discrete finite element approximation of the unsteady p(·,·)-Stokes equations. CoRR Luigi C. Berselli, Alex Kaltenbach, Seungchan Ko
2025	J	`jnl`	Finite Element Operator Network for Solving Elliptic-Type Parametric PDEs. SIAM J. Sci. Comput. Jae Yong Lee, Seungchan Ko, Youngjoon Hong
2025	J	`jnl`	Locking-Free Training of Physics-Informed Neural Network for Solving Nearly Incompressible Elasticity Equations. CoRR Josef Dick, Seungchan Ko, Kassem Mustapha, Sanghyeon Park
2025	J	`jnl`	VS-PINN: A fast and efficient training of physics-informed neural networks using variable-scaling methods for solving PDEs with stiff behavior. J. Comput. Phys. Seungchan Ko, Sanghyeon Park
2024	J	`jnl`	Error analysis for finite element operator learning methods for solving parametric second-order elliptic PDEs. CoRR Youngjoon Hong, Seungchan Ko, Jae Yong Lee
2024	J	`jnl`	VS-PINN: A Fast and efficient training of physics-informed neural networks using variable-scaling methods for solving PDEs with stiff behavior. CoRR Seungchan Ko, Sang Hyeon Park
2023	J	`jnl`	A novel approach for wafer defect pattern classification based on topological data analysis. Expert Syst. Appl. Seungchan Ko, Dowan Koo
2023	J	`jnl`	Finite Element Operator Network for Solving Parametric PDEs. CoRR Jae Yong Lee, Seungchan Ko, Youngjoon Hong
2022	J	`jnl`	A novel approach for wafer defect pattern classification based on topological data analysis. CoRR Seungchan Ko, Dowan Koo
2022	J	`jnl`	Convergence analysis of unsupervised Legendre-Galerkin neural networks for linear second-order elliptic PDEs. CoRR Seungchan Ko, Seok-Bae Yun, Youngjoon Hong
2022	J	`jnl`	Quasi-Monte Carlo finite element approximation of the Navier-Stokes equations with initial data modeled by log-normal random fields. CoRR Seungchan Ko, Guanglian Li, Yi Yu
2019	J	`jnl`	Finite element approximation of steady flows of generalized Newtonian fluids with concentration-dependent power-law index. Math. Comput. Seungchan Ko, Endre Süli