Time Series Forecasting with Hypernetworks Generating Parameters in Advance. - Jaehoon Lee 002; Chan Kim; Gyumin Lee; Haksoo Lim; Jeongwhan Choi 002; Kookjin Lee; Dongeun Lee 001; Sanghyun Hong 001; Noseong Park (CoRR, 2022)

Long-term Time Series Forecasting based on Decomposition and Neural Ordinary Differential Equations. - Seonkyu Lim; Jaehyeon Park; Seojin Kim; Hyowon Wi; Haksoo Lim; Jinsung Jeon; Jeongwhan Choi 002; Noseong Park (IEEE Big Data, 2023)

MadSGM: Multivariate Anomaly Detection with Score-based Generative Models. - Haksoo Lim; Sewon Park 004; Minjung Kim; Jaehoon Lee 002; Seonkyu Lim; Noseong Park (CIKM, 2023)

Regular Time-series Generation using SGM. - Haksoo Lim; Minjung Kim; Sewon Park 004; Noseong Park (CoRR, 2023)

Parameterized Physics-informed Neural Networks for Parameterized PDEs. - Woojin Cho; Minju Jo; Haksoo Lim; Kookjin Lee; Dongeun Lee 001; Sanghyun Hong 001; Noseong Park (ICML, 2024)

Efficiently Parameterized Neural Metriplectic Systems. - Anthony Gruber; Kookjin Lee; Haksoo Lim; Noseong Park; Nathaniel Trask (ICLR, 2025)