5 papers
CAAD: Causality-Aware Multivariate Time Series Anomaly Detection via Multi-Scale Alignment and Structural Causal Consistency
Xin Wang, Yunshi Wen, Yanan He +4
The operational integrity of complex industrial systems relies on precise anomaly detection and diagnosis. The vast majority of existing methods narrowly focus on capturing tempora…
SC-JEPA: Stabilizing Latent Predictive Learning for Time-Series Anomaly Prediction
Yanan He, Yunshi Wen, Xin Wang +1
Time-series anomaly prediction aims to forecast future system failures before they fully emerge, making latent predictive models such as JEPA a promising framework for capturing pr…
Sparse-Group Factor Analysis for High-Dimensional Time Series
Xin Wang, Xialu Liu
Factor analysis is a widely used technique for dimension reduction in high-dimensional data. However, a key challenge in factor models lies in the interpretability of the latent fa…
Prediction of high-frequency futures return directions based on the mean uncertainty classification methods: An application in China's future market
Ying Peng, Yifan Zhang, Xin Wang
In this paper, we mainly focus on the prediction of short-term average return directions in China's high-frequency futures market. As minor fluctuations with limited amplitude and…
Regularized Estimation of the Loading Matrix in Factor Models for High-Dimensional Time Series
Xialu Liu, Xin Wang
High-dimensional data analysis using traditional models suffers from overparameterization. Two types of techniques are commonly used to reduce the number of parameters - regulariza…