Youngjoon Hong

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 39

Top Topics

Image Magnification

Boundary Value Problem

Differential Equations

Top Venues

J. Comput. Phys.

J. Sci. Comput.

Publications

Teng-Yuan Chang, Gung-Min Gie, Youngjoon Hong, Chang-Yeol Jung
Singular layer physics informed neural network method for plane parallel flows. Comput. Math. Appl. 166 (2024)
Sanghyeon Kim, Hyunmo Yang, Yunghyun Kim, Youngjoon Hong, Eunbyung Park
Hydra: Multi-head low-rank adaptation for parameter efficient fine-tuning. Neural Networks 178 (2024)
Jaemin Oh, Seung-Yeon Cho, Seok-Bae Yun, Eunbyung Park, Youngjoon Hong
Separable Physics-informed Neural Networks for Solving the BGK Model of the Boltzmann Equation. CoRR (2024)
Youngjoon Hong, Seungchan Ko, Jae Yong Lee
Error analysis for finite element operator learning methods for solving parametric second-order elliptic PDEs. CoRR (2024)
Yunchang Seol, Suho Kim, Minwoo Jung, Youngjoon Hong
A novel physics-aware graph network using high-order numerical methods in weather forecasting model. Knowl. Based Syst. 300 (2024)
Gung-Min Gie, Youngjoon Hong, Chang-Yeol Jung, Tselmuun Munkhjin
Semi-analytic PINN methods for boundary layer problems in a rectangular domain. J. Comput. Appl. Math. 450 (2024)
Soohan Kim, Jimyeong Kim, Hong Kee Sul, Youngjoon Hong
An adaptive dual-level reinforcement learning approach for optimal trade execution. Expert Syst. Appl. 252 (2024)
Namgyu Kang, Byeonghyeon Lee, Youngjoon Hong, Seok-Bae Yun, Eunbyung Park
PIXEL: Physics-Informed Cell Representations for Fast and Accurate PDE Solvers. AAAI (2023)
Sanghyeon Kim, Hyunmo Yang, Younghyun Kim, Youngjoon Hong, Eunbyung Park
Hydra: Multi-head Low-rank Adaptation for Parameter Efficient Fine-tuning. CoRR (2023)
Jae Yong Lee, Seungchan Ko, Youngjoon Hong
Finite Element Operator Network for Solving Parametric PDEs. CoRR (2023)
Gung-Min Gie, Youngjoon Hong, Chang-Yeol Jung, Dongseok Lee
Semi-analytic physics informed neural network for convection-dominated boundary layer problems in 2D. CoRR (2023)
Junho Choi, Taehyun Yun, Namjung Kim, Youngjoon Hong
Spectral operator learning for parametric PDEs without data reliance. CoRR (2023)
Junwoo Cho, Seungtae Nam, Hyunmo Yang, Seok-Bae Yun, Youngjoon Hong, Eunbyung Park
Separable Physics-Informed Neural Networks. CoRR (2023)
Junwoo Cho, Seungtae Nam, Hyunmo Yang, Seok-Bae Yun, Youngjoon Hong, Eunbyung Park
Separable Physics-Informed Neural Networks. NeurIPS (2023)
Gung-Min Gie, Youngjoon Hong, Chang-Yeol Jung, Tselmuun Munkhjin
Semi-analytic PINN methods for boundary layer problems in a rectangular domain. CoRR (2023)
Teng-Yuan Chang, Gung-Min Gie, Youngjoon Hong, Chang-Yeol Jung
Singular layer Physics Informed Neural Network method for Plane Parallel Flows. CoRR (2023)
Junho Choi, Namjung Kim, Youngjoon Hong
Unsupervised Legendre-Galerkin Neural Network for Solving Partial Differential Equations. IEEE Access 11 (2023)
Seungchan Ko, Seok-Bae Yun, Youngjoon Hong
Convergence analysis of unsupervised Legendre-Galerkin neural networks for linear second-order elliptic PDEs. CoRR (2022)
Byeongkeun Ahn, Chiyoon Kim, Youngjoon Hong, Hyunwoo J. Kim
Invertible Monotone Operators for Normalizing Flows. CoRR (2022)
Byeongkeun Ahn, Chiyoon Kim, Youngjoon Hong, Hyunwoo J. Kim
Invertible Monotone Operators for Normalizing Flows. NeurIPS (2022)
Namgyu Kang, Byeonghyeon Lee, Youngjoon Hong, Seok-Bae Yun, Eunbyung Park
PIXEL: Physics-Informed Cell Representations for Fast and Accurate PDE Solvers. CoRR (2022)
Gung-Min Gie, Youngjoon Hong, Chang-Yeol Jung
Semi-analytic PINN methods for singularly perturbed boundary value problems. CoRR (2022)
Junho Choi, Namjung Kim, Youngjoon Hong
Unsupervised Legendre-Galerkin Neural Network for Stiff Partial Differential Equations. CoRR (2022)
Junwoo Cho, Seungtae Nam, Hyunmo Yang, Seok-Bae Yun, Youngjoon Hong, Eunbyung Park
Separable PINN: Mitigating the Curse of Dimensionality in Physics-Informed Neural Networks. CoRR (2022)
Youngjoon Hong, David P. Nicholls
A Rigorous Numerical Analysis of the Transformed Field Expansion Method for Diffraction by Periodic, Layered Structures. SIAM J. Numer. Anal. 59 (1) (2021)
Hyun-Myung Woo, Youngjoon Hong, Bongsuk Kwon, Byung-Jun Yoon
Accelerating Optimal Experimental Design for Robust Synchronization of Uncertain Kuramoto Oscillator Model Using Machine Learning. IEEE Trans. Signal Process. 69 (2021)
Youngjoon Hong, Bongsuk Kwon, Byung-Jun Yoon
Optimal Experimental Design for Uncertain Systems Based on Coupled Differential Equations. IEEE Access 9 (2021)
Hwan Heo, Dohwan Ko, Jaewon Lee, Youngjoon Hong, Hyunwoo J. Kim
Search-and-Attack: Temporally Sparse Adversarial Perturbations on Videos. IEEE Access 9 (2021)
Byungjoo Kim, Bryce Chudomelka, Jinyoung Park, Jaewoo Kang, Youngjoon Hong, Hyunwoo J. Kim
Robust Neural Networks Inspired by Strong Stability Preserving Runge-Kutta Methods. ECCV (9) (2020)
Bryce Chudomelka, Youngjoon Hong, Hyunwoo J. Kim, Jinyoung Park
Deep neural network for solving differential equations motivated by Legendre-Galerkin approximation. CoRR (2020)
Mickaël D. Chekroun, Youngjoon Hong, Roger Temam
Enriched numerical scheme for singularly perturbed barotropic Quasi-Geostrophic equations. J. Comput. Phys. 416 (2020)
Youngjoon Hong, Bongsuk Kwon, Byung-Jun Yoon
Optimal Experimental Design for Uncertain Systems Based on Coupled Differential Equations. CoRR (2020)
Arthur Bousquet, Youngjoon Hong, Roger Temam, Joseph J. Tribbia
Numerical Simulations of the Two-Dimensional Inviscid Hydrostatic Primitive Equations with Humidity and Saturation. J. Sci. Comput. 83 (2) (2020)
Byungjoo Kim, Bryce Chudomelka, Jinyoung Park, Jaewoo Kang, Youngjoon Hong, Hyunwoo J. Kim
Robust Neural Networks inspired by Strong Stability Preserving Runge-Kutta methods. CoRR (2020)
Youngjoon Hong, David P. Nicholls
A high-order perturbation of surfaces method for vector electromagnetic scattering by doubly layered periodic crossed gratings. J. Comput. Phys. 372 (2018)
Youngjoon Hong, Chang-Yeol Jung
Enriched Spectral Method for Stiff Convection-Dominated Equations. J. Sci. Comput. 74 (3) (2018)
Youngjoon Hong, David P. Nicholls
A stable high-order perturbation of surfaces method for numerical simulation of diffraction problems in triply layered media. J. Comput. Phys. 330 (2017)
Youngjoon Hong, David P. Nicholls
A high-order perturbation of surfaces method for scattering of linear waves by periodic multiply layered gratings in two and three dimensions. J. Comput. Phys. 345 (2017)
Youngjoon Hong
Global attractor of atmospheric equations. Asymptot. Anal. 96 (2) (2016)
Youngjoon Hong
Numerical Approximation of the Singularly Perturbed Heat Equation in a Circle. J. Sci. Comput. 62 (1) (2015)
Arthur Bousquet, Gung-Min Gie, Youngjoon Hong, Jacques Laminie
A higher order Finite Volume resolution method for a system related to the inviscid primitive equations in a complex domain. Numerische Mathematik 128 (3) (2014)
Youngjoon Hong, Chang-Yeol Jung, Roger Temam
On the numerical approximations of stiff convection-diffusion equations in a circle. Numerische Mathematik 127 (2) (2014)
Youngjoon Hong, Chang-Yeol Jung, Jacques Laminie
Singularly perturbed reaction-diffusion equations in a circle with numerical applications. Int. J. Comput. Math. 90 (11) (2013)
Qingshan Chen, Youngjoon Hong, Roger Temam
Analysis of a Penalty Method. J. Sci. Comput. 53 (1) (2012)