5 citations · 5 across the 4 of their papers we have counts for
4 papers
Impute On-Demand: Adaptive Correlated Time Series Imputation for Changing Environments
Zhichen Lai, Huan Li, Dalin Zhang +3
Internet of Things (IoT) applications generate vast amounts of Correlated Time Series (CTS) data that often contain missing values and require imputation. Existing methods emphasiz…
MovSemCL: Movement-Semantics Contrastive Learning for Trajectory Similarity (Extension)
Zhichen Lai, Hua Lu, Huan Li +2
Trajectory similarity computation is fundamental functionality that is used for, e.g., clustering, prediction, and anomaly detection. However, existing learning-based methods exhib…
E2USD: Efficient-yet-effective Unsupervised State Detection for Multivariate Time Series
Zhichen Lai, Huan Li, Dalin Zhang +3
Cyber-physical system sensors emit multivariate time series (MTS) that monitor physical system processes. Such time series generally capture unknown numbers of states, each with a…
LightCTS: A Lightweight Framework for Correlated Time Series Forecasting
Zhichen Lai, Dalin Zhang, Huan Li +3
Correlated time series (CTS) forecasting plays an essential role in many practical applications, such as traffic management and server load control. Many deep learning models have…