no code implementations • 18 Aug 2024 • Woojin Cho, Minju Jo, Haksoo Lim, Kookjin Lee, Dongeun Lee, Sanghyun Hong, Noseong Park
Complex physical systems are often described by partial differential equations (PDEs) that depend on parameters such as the Reynolds number in fluid mechanics.
no code implementations • 25 May 2024 • Anthony Gruber, Kookjin Lee, Haksoo Lim, Noseong Park, Nathaniel Trask
Metriplectic systems are learned from data in a way that scales quadratically in both the size of the state and the rank of the metriplectic data.
no code implementations • 8 Nov 2023 • Seonkyu Lim, Jaehyeon Park, Seojin Kim, Hyowon Wi, Haksoo Lim, Jinsung Jeon, Jeongwhan Choi, Noseong Park
Long-term time series forecasting (LTSF) is a challenging task that has been investigated in various domains such as finance investment, health care, traffic, and weather forecasting.
no code implementations • 29 Aug 2023 • Haksoo Lim, Sewon Park, Minjung Kim, Jaehoon Lee, Seonkyu Lim, Noseong Park
The time-series anomaly detection is one of the most fundamental tasks for time-series.
no code implementations • 20 Jan 2023 • Haksoo Lim, Minjung Kim, Sewon Park, Noseong Park
We propose a conditional score network for the time-series generation domain.
no code implementations • 22 Nov 2022 • Jaehoon Lee, Chan Kim, Gyumin Lee, Haksoo Lim, Jeongwhan Choi, Kookjin Lee, Dongeun Lee, Sanghyun Hong, Noseong Park
Forecasting future outcomes from recent time series data is not easy, especially when the future data are different from the past (i. e. time series are under temporal drifts).