22 citations · 36 across the 8 of their papers we have counts for
8 papers
TSGM: Regular and Irregular Time-series Generation using Score-based Generative Models
Haksoo Lim, Jaehoon Lee, Sewon Park +2
Score-based generative models (SGMs) have demonstrated unparalleled sampling quality and diversity in numerous fields, such as image generation, voice synthesis, and tabular data s…
MadSGM: Multivariate Anomaly Detection with Score-based Generative Models
Haksoo Lim, Sewon Park, Minjung Kim +3
The time-series anomaly detection is one of the most fundamental tasks for time-series. Unlike the time-series forecasting and classification, the time-series anomaly detection typ…
Precursor-of-Anomaly Detection for Irregular Time Series
Sheo Yon Jhin, Jaehoon Lee, Noseong Park
Anomaly detection is an important field that aims to identify unexpected patterns or data points, and it is closely related to many real-world problems, particularly to application…
Time Series Forecasting with Hypernetworks Generating Parameters in Advance
Jaehoon Lee, Chan Kim, Gyumin Lee +6
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). Exis…
LORD: Lower-Dimensional Embedding of Log-Signature in Neural Rough Differential Equations
Jaehoon Lee, Jinsung Jeon, Sheo yon Jhin +5
The problem of processing very long time-series data (e.g., a length of more than 10,000) is a long-standing research problem in machine learning. Recently, one breakthrough, calle…
EXIT: Extrapolation and Interpolation-based Neural Controlled Differential Equations for Time-series Classification and Forecasting
Sheo Yon Jhin, Jaehoon Lee, Minju Jo +5
Deep learning inspired by differential equations is a recent research trend and has marked the state of the art performance for many machine learning tasks. Among them, time-series…
Invertible Tabular GANs: Killing Two Birds with OneStone for Tabular Data Synthesis
Jaehoon Lee, Jihyeon Hyeong, Jinsung Jeon +2
Tabular data synthesis has received wide attention in the literature. This is because available data is often limited, incomplete, or cannot be obtained easily, and data privacy is…
OCT-GAN: Neural ODE-based Conditional Tabular GANs
Jayoung Kim, Jinsung Jeon, Jaehoon Lee +2
Synthesizing tabular data is attracting much attention these days for various purposes. With sophisticate synthetic data, for instance, one can augment its training data. For the p…