| Trend to equilibrium for the kinetic Fokker-Planck equation via the neural network approach HJ Hwang, JW Jang, H Jo, JY Lee Journal of Computational Physics 419, 109665, 2020 | 33 | 2020 |
| Solving pde-constrained control problems using operator learning R Hwang, JY Lee, JY Shin, HJ Hwang Proceedings of the AAAI Conference on Artificial Intelligence 36 (4), 4504-4512, 2022 | 15 | 2022 |
| The model reduction of the Vlasov-Poisson-Fokker-Planck system to the Poisson-Nernst-Planck system via the Deep Neural Network Approach JY Lee, JW Jang, HJ Hwang ESAIM: Mathematical Modelling and Numerical Analysis (ESAIM: M2AN) 55 (5 …, 2021 | 12 | 2021 |
| HyperDeepONet: learning operator with complex target function space using the limited resources via hypernetwork JY Lee, CHO SungWoong, HJ Hwang The Eleventh International Conference on Learning Representations, 2022 | 3 | 2022 |
| Pseudo-Differential Integral Operator for Learning Solution Operators of Partial Differential Equations JY Shin, JY Lee, HJ Hwang arXiv preprint arXiv:2201.11967, 2022 | 1 | 2022 |
| Finite Element Operator Network for Solving Parametric PDEs JY Lee, S Ko, Y Hong arXiv preprint arXiv:2308.04690, 2023 | | 2023 |
| 물리 정보 기계학습의 발전 및 응용 이재용， 손휘재 전자공학회지 50 (No.6), 50-58, 2023 | | 2023 |
| opPINN: Physics-informed neural network with operator learning to approximate solutions to the Fokker-Planck-Landau equation JY Lee, J Jang, HJ Hwang Journal of Computational Physics 480, 112031, 2023 | | 2023 |
Hyung Ju HwangProfessor and Chair Professor, POSTECHpostech.ac.kr의 이메일 확인됨
