5 papers
When Prediction Shapes the Future: A BlueSky Agenda for Reflexive Time Series Analysis
Tao Xie, Yiqun Zhang, Yiu-ming Cheung
Time-series models are increasingly deployed in operational systems (e.g., inventory management and clinical care) where predictions trigger interventions that alter future observa…
AnchorMoE: Interpretable Time Series Classification via Anchor-Routed MoE
Tao Xie, Zexi Tan, Haoyi Xiao +5
Multivariate time series classification (MTSC) is pivotal in high-stakes domains, such as clinical diagnosis and industrial fault detection, where safe deployment necessitates tran…
TFEC: Multivariate Time-Series Clustering via Temporal-Frequency Enhanced Contrastive Learning
Zexi Tan, Tao Xie, Haoyi Xiao +5
Multivariate Time-Series (MTS) clustering is crucial for signal processing and data analysis. Although deep learning approaches, particularly those leveraging Contrastive Learning…
DE3S: Dual-Enhanced Soft-Sparse-Shape Learning for Medical Early Time-Series Classification
Tao Xie, Zexi Tan, Haoyi Xiao +2
Early Time Series Classification (ETSC) is critical in time-sensitive medical applications such as sepsis, yet it presents an inherent trade-off between accuracy and earliness. Thi…
MEET-Sepsis: Multi-Endogenous-View Enhanced Time-Series Representation Learning for Early Sepsis Prediction
Zexi Tan, Tao Xie, Binbin Sun +3
Sepsis is a life-threatening infectious syndrome associated with high mortality in intensive care units (ICUs). Early and accurate sepsis prediction (SP) is critical for timely int…