Jae Yong Lee

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Hyung Ju HwangProfessor and Director for CM2LA, POSTECHVerified email at postech.ac.kr
Jin Woo JangPohang University of Science and Technology, Department of MathematicsVerified email at math.upenn.edu
Hyeontae JoInstitute for Basic Science (IBS)Verified email at ibs.re.kr
Rakhoon HwangHyundai Motor CompanyVerified email at hyundai.com
Seungchan KoInha UniversityVerified email at inha.ac.kr
Youngjoon HongKAISTVerified email at kaist.ac.kr
Steffen SchotthöferHouseholder Fellow, Oak Ridge National LaboratoryVerified email at ornl.gov
Tianbai XiaoProfessor, Chinese Academy of SciencesVerified email at imech.ac.cn
Martin FrankComputational Science & Mathematical Methods, Steinbuch Center for Computing, Karlsruhe Institute of TechnologyVerified email at kit.edu
Hwijae SonKonkuk UniversityVerified email at konkuk.ac.kr
Sebastian KrumscheidKarlsruhe Institute of TechnologyVerified email at kit.edu

Jae Yong Lee

Assistant Professor, Department of AI, Chung-Ang University

Verified email at cau.ac.kr - Homepage

Scientific Machine Learning Physics-Informed Machine Learning Neural PDE solver AI for Science


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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	30	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	25	2022
HyperDeepONet: learning operator with complex target function space using the limited resources via hypernetwork JY Lee, SW Cho, HJ Hwang International Conference on Learning Representations, 2023	15	2023
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	15	2021
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	5	2023
Pseudo-Differential Neural Operator: Generalize Fourier Neural operator for Learning Solution Operators of Partial Differential Equations JY Shin, JY Lee, HJ Hwang Transactions on Machine Learning Research (TMLR), 2024	3*	2024
Finite element operator network for solving parametric pdes JY Lee, S Ko, Y Hong arXiv preprint arXiv:2308.04690, 2023	3	2023
Error analysis for finite element operator learning methods for solving parametric second-order elliptic PDEs Y Hong, S Ko, J Lee arXiv preprint arXiv:2404.17868, 2024		2024
Structure-Preserving Operator Learning: Modeling the Collision Operator of Kinetic Equations JY Lee, S Schotthöfer, T Xiao, S Krumscheid, M Frank arXiv preprint arXiv:2402.16613, 2024		2024
Learning time-dependent PDE via graph neural networks and deep operator network for robust accuracy on irregular grids SW Cho, JY Lee, HJ Hwang arXiv preprint arXiv:2402.08187, 2024		2024
물리 정보 기계학습의 발전 및 응용 이재용， 손휘재 전자공학회지 50 (No.6), 50-58, 2023		2023

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