4 citations · 11 across the 5 of their papers we have counts for
5 papers
KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks
Quan Zhou, Changhua Pei, Fei Sun +6
Time series anomaly detection (TSAD) underpins real-time monitoring in cloud services and web systems, allowing rapid identification of anomalies to prevent costly failures. Most T…
Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective
Zexin Wang, Changhua Pei, Minghua Ma +9
Time series Anomaly Detection (AD) plays a crucial role for web systems. Various web systems rely on time series data to monitor and identify anomalies in real time, as well as to…
TimeSeriesBench: An Industrial-Grade Benchmark for Time Series Anomaly Detection Models
Haotian Si, Jianhui Li, Changhua Pei +9
Time series anomaly detection (TSAD) has gained significant attention due to its real-world applications to improve the stability of modern software systems. However, there is no e…
OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models
Yuhe Liu, Changhua Pei, Longlong Xu +13
Information Technology (IT) Operations (Ops), particularly Artificial Intelligence for IT Operations (AIOps), is the guarantee for maintaining the orderly and stable operation of e…
Beyond Sharing: Conflict-Aware Multivariate Time Series Anomaly Detection
Haotian Si, Changhua Pei, Zhihan Li +7
Massive key performance indicators (KPIs) are monitored as multivariate time series data (MTS) to ensure the reliability of the software applications and service system. Accurately…