4 citations · 8 across the 10 of their papers we have counts for
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cs.LG2024
A New Perspective on Time Series Anomaly Detection: Faster Patch-based Broad Learning System
Pengyu Li, Zhijie Zhong, Tong Zhang +3
Time series anomaly detection (TSAD) has been a research hotspot in both academia and industry in recent years. Deep learning methods have become the mainstream research direction…
cs.LG2024★ 4 cited
SimAD: A Simple Dissimilarity-based Approach for Time Series Anomaly Detection
Zhijie Zhong, Zhiwen Yu, Xing Xi +5
Despite the prevalence of reconstruction-based deep learning methods, time series anomaly detection remains a tremendous challenge. Existing approaches often struggle with limited…
cs.LG2024★ 4 cited
PatchAD: A Lightweight Patch-based MLP-Mixer for Time Series Anomaly Detection
Zhijie Zhong, Zhiwen Yu, Yiyuan Yang +2
Time series anomaly detection is a pivotal task in data analysis, yet it poses the challenge of discerning normal and abnormal patterns in label-deficient scenarios. While prior st…