Lee, Kookjin

20 publications

ICLR 2025 Efficiently Parameterized Neural Metriplectic Systems Anthony Gruber, Kookjin Lee, Haksoo Lim, Noseong Park, Nathaniel Trask

TMLR 2025 Latent Space Energy-Based Neural ODEs Sheng Cheng, Deqian Kong, Jianwen Xie, Kookjin Lee, Ying Nian Wu, Yezhou Yang

ICLR 2025 Neural Functions for Learning Periodic Signal Woojin Cho, Minju Jo, Kookjin Lee, Noseong Park

NeurIPS 2025 PDEfuncta: Spectrally-Aware Neural Representation for PDE Solution Modeling Minju Jo, Woojin Cho, Uvini Balasuriya Mudiyanselage, Seungjun Lee, Noseong Park, Kookjin Lee

ICLR 2025 PIORF: Physics-Informed Ollivier-Ricci Flow for Long–Range Interactions in Mesh Graph Neural Networks Youn-Yeol Yu, Jeongwhan Choi, Jaehyeon Park, Kookjin Lee, Noseong Park

ICLRW 2025 Unveiling the Potential of Superexpressive Networks in Implicit Neural Representations Uvini Balasuriya Mudiyanselage, Woojin Cho, Minju Jo, Noseong Park, Kookjin Lee

NeurIPSW 2024 Can We Pre-Train ICL-Based SFMs for the Zero-Shot Inference of the 1d CDR Problem with Noisy Data? Mingu Kang, Dongseok Lee, Woojin Cho, Kookjin Lee, Anthony Gruber, Nathaniel Trask, Youngjoon Hong, Noseong Park

ICLRW 2024 Extension of Physics-Informed Neural Networks to Solving Parameterized PDEs Woojin Cho, Minju Jo, Haksoo Lim, Kookjin Lee, Dongeun Lee, Sanghyun Hong, Noseong Park

NeurIPS 2024 Graph Convolutions Enrich the Self-Attention in Transformers! Jeongwhan Choi, Hyowon Wi, Jayoung Kim, Yehjin Shin, Kookjin Lee, Nathaniel Trask, Noseong Park

ICLR 2024 Learning Flexible Body Collision Dynamics with Hierarchical Contact Mesh Transformer Youn-Yeol Yu, Jeongwhan Choi, Woojin Cho, Kookjin Lee, Nayong Kim, Kiseok Chang, ChangSeung Woo, Ilho Kim, SeokWoo Lee, Joon Young Yang, Sooyoung Yoon, Noseong Park

AAAI 2024 Operator-Learning-Inspired Modeling of Neural Ordinary Differential Equations Woojin Cho, Seunghyeon Cho, Hyundong Jin, Jinsung Jeon, Kookjin Lee, Sanghyun Hong, Dongeun Lee, Jonghyun Choi, Noseong Park

ICLR 2024 PAC-FNO: Parallel-Structured All-Component Fourier Neural Operators for Recognizing Low-Quality Images Jinsung Jeon, Hyundong Jin, Jonghyun Choi, Sanghyun Hong, Dongeun Lee, Kookjin Lee, Noseong Park

ICML 2024 Parameterized Physics-Informed Neural Networks for Parameterized PDEs Woojin Cho, Minju Jo, Haksoo Lim, Kookjin Lee, Dongeun Lee, Sanghyun Hong, Noseong Park

NeurIPSW 2023 HyperNetwork Approximating Future Parameters for Time Series Forecasting Under Temporal Drifts Jaehoon Lee, Chan Kim, Gyumin Lee, Haksoo Lim, Jeongwhan Choi, Kookjin Lee, Dongeun Lee, Sanghyun Hong, Noseong Park

NeurIPS 2023 Hypernetwork-Based Meta-Learning for Low-Rank Physics-Informed Neural Networks Woojin Cho, Kookjin Lee, Donsub Rim, Noseong Park

NeurIPS 2023 Reversible and Irreversible Bracket-Based Dynamics for Deep Graph Neural Networks Anthony Gruber, Kookjin Lee, Nathaniel Trask

ICML 2021 A Novel Method to Solve Neural Knapsack Problems Duanshun Li, Jing Liu, Dongeun Lee, Ali Seyedmazloom, Giridhar Kaushik, Kookjin Lee, Noseong Park

AAAI 2021 DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation Jungeun Kim, Kookjin Lee, Dongeun Lee, Sheo Yon Jhin, Noseong Park

AAAI 2021 Deep Conservation: A Latent-Dynamics Model for Exact Satisfaction of Physical Conservation Laws Kookjin Lee, Kevin T. Carlberg

NeurIPS 2021 Machine Learning Structure Preserving Brackets for Forecasting Irreversible Processes Kookjin Lee, Nathaniel Trask, Panos Stinis