Jae Yong Lee

18 papers A* 2Journal 15Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Learning time-dependent PDE via graph neural networks and deep operator network for robust accuracy on irregular grids.
J. Comput. Phys.
Sung Woong Cho, Jae Yong Lee, Hyung Ju Hwang
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
Hamilton-Jacobi based policy-iteration via deep operator learning.
Neurocomputing
Jae Yong Lee, Yeoneung Kim
2025 — conf
Physics-Informed Neural Operators for Tissue Elasticity Reconstruction.
MICCAI (10)
Youjin Kim, Jae Yong Lee, Junseok Kwon
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
Learning time-dependent PDE via graph neural networks and deep operator network for robust accuracy on irregular grids.
CoRR
Sung Woong Cho, Jae Yong Lee, Hyung Ju Hwang
2024 J jnl
Pseudo-Differential Neural Operator: Generalize Fourier Neural operator for Learning Solution Operators of Partial Differential Equations.
Trans. Mach. Learn. Res.
Jinyoung Shin, Jae Yong Lee, Hyung Ju Hwang
2023 J jnl
Finite Element Operator Network for Solving Parametric PDEs.
CoRR
Jae Yong Lee, Seungchan Ko, Youngjoon Hong
2023 A* conf
HyperDeepONet: learning operator with complex target function space using the limited resources via hypernetwork.
ICLR
Jae Yong Lee, Sung Woong Cho, Hyung Ju Hwang
2023 J jnl
HyperDeepONet: learning operator with complex target function space using the limited resources via hypernetwork.
CoRR
Jae Yong Lee, Sung Woong Cho, Hyung Ju Hwang
2023 J jnl
opPINN: Physics-informed neural network with operator learning to approximate solutions to the Fokker-Planck-Landau equation.
J. Comput. Phys.
Jae Yong Lee, Juhi Jang, Hyung Ju Hwang
2022 J jnl
Pseudo-Differential Integral Operator for Learning Solution Operators of Partial Differential Equations.
CoRR
Jinyoung Shin, Jae Yong Lee, Hyung Ju Hwang
2022 A* conf
Solving PDE-Constrained Control Problems Using Operator Learning.
AAAI
Rakhoon Hwang, Jae Yong Lee, Jinyoung Shin, Hyung Ju Hwang
2022 J jnl
opPINN: Physics-Informed Neural Network with operator learning to approximate solutions to the Fokker-Planck-Landau equation.
CoRR
Jae Yong Lee, Juhi Jang, Hyung Ju Hwang
2021 J jnl
Solving PDE-constrained Control Problems using Operator Learning.
CoRR
Rakhoon Hwang, Jae Yong Lee, Jinyoung Shin, Hyung Ju Hwang
2020 J jnl
The model reduction of the Vlasov-Poisson-Fokker-Planck system to the Poisson-Nernst-Planck system via the Deep Neural Network Approach.
CoRR
Jae Yong Lee, Jin Woo Jang, Hyung Ju Hwang
2020 J jnl
Trend to equilibrium for the kinetic Fokker-Planck equation via the neural network approach.
J. Comput. Phys.
Hyung Ju Hwang, Jin Woo Jang, Hyeontae Jo, Jae Yong Lee
2019 J jnl
Trend to Equilibrium for the Kinetic Fokker-Planck Equation via the Neural Network Approach.
CoRR
Hyung Ju Hwang, Jin Woo Jang, Hyeontae Jo, Jae Yong Lee