32 citations · 37 across the 8 of their papers we have counts for
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cs.LG2024
Large Language Model Guided Knowledge Distillation for Time Series Anomaly Detection
Chen Liu, Shibo He, Qihang Zhou +2
Self-supervised methods have gained prominence in time series anomaly detection due to the scarcity of available annotations. Nevertheless, they typically demand extensive training…
cs.LG2023★ 2 cited
Label-Free Multivariate Time Series Anomaly Detection
Qihang Zhou, Shibo He, Haoyu Liu +2
Anomaly detection in multivariate time series (MTS) has been widely studied in one-class classification (OCC) setting. The training samples in OCC are assumed to be normal, which i…
cs.LG2022
Detecting Multivariate Time Series Anomalies with Zero Known Label
Qihang Zhou, Jiming Chen, Haoyu Liu +2
Multivariate time series anomaly detection has been extensively studied under the semi-supervised setting, where a training dataset with all normal instances is required. However,…