4 papers
STAG: Structural Test-time Alignment of Gradients for Online Adaptation
Juhyeon Shin, Yujin Oh, Jonghyun Lee +5
Test-Time Adaptation (TTA) adapts pre-trained models using only unlabeled test streams, requiring real-time inference and update without access to source data. We propose Structura…
Causality-Aware Contrastive Learning for Robust Multivariate Time-Series Anomaly Detection
HyunGi Kim, Jisoo Mok, Dongjun Lee +3
Utilizing the complex inter-variable causal relationships within multivariate time-series provides a promising avenue toward more robust and reliable multivariate time-series anoma…
A Comprehensive Survey of Deep Learning for Time Series Forecasting: Architectural Diversity and Open Challenges
Jongseon Kim, Hyungjoon Kim, HyunGi Kim +2
Time series forecasting is a critical task that provides key information for decision-making. After traditional statistical and machine learning approaches, various fundamental dee…
Introducing Spectral Attention for Long-Range Dependency in Time Series Forecasting
Bong Gyun Kang, Dongjun Lee, HyunGi Kim +2
Sequence modeling faces challenges in capturing long-range dependencies across diverse tasks. Recent linear and transformer-based forecasters have shown superior performance in tim…