Time Series

We propose AdaCGP, an online algorithm that adaptively estimates graph shift operators from streaming multivariate time series using time-vertex autoregressive models. The method achieves 82% improvement over baseline adaptive VAR models in graph structure recovery and demonstrates clinical utility in tracking ventricular fibrillation dynamics under anti-arrhythmic treatment.

We introduce PulseDiff, a diffusion-based approach for ECG signal imputation that leverages subject-specific pulse templates as informative priors. Our method outperforms leading deterministic models for short-interval missing data and achieves comparable performance for long-interval data loss, addressing key challenges in mobile health monitoring.