10 citations · 14 across the 4 of their papers we have counts for
4 papers
When Model Meets New Normals: Test-time Adaptation for Unsupervised Time-series Anomaly Detection
Dongmin Kim, Sunghyun Park, Jaegul Choo
Time-series anomaly detection deals with the problem of detecting anomalous timesteps by learning normality from the sequence of observations. However, the concept of normality evo…
Deep Imbalanced Time-series Forecasting via Local Discrepancy Density
Junwoo Park, Jungsoo Lee, Youngin Cho +4
Time-series forecasting models often encounter abrupt changes in a given period of time which generally occur due to unexpected or unknown events. Despite their scarce occurrences…
WaveBound: Dynamic Error Bounds for Stable Time Series Forecasting
Youngin Cho, Daejin Kim, Dongmin Kim +2
Time series forecasting has become a critical task due to its high practicality in real-world applications such as traffic, energy consumption, economics and finance, and disease a…
Residual Correction in Real-Time Traffic Forecasting
Daejin Kim, Youngin Cho, Dongmin Kim +2
Predicting traffic conditions is tremendously challenging since every road is highly dependent on each other, both spatially and temporally. Recently, to capture this spatial and t…