arXiv cs.LG
· Papers
SC-JEPA: Stabilizing Latent Predictive Learning for Time-Series Anomaly Prediction
arXiv:2602.04643v2 Announce Type: replace Abstract: 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 precursor dynamics. However, directly applying continuous self-distillation to time-series