Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder

Author:

Li Zeyan,Chen Wenxiao,Pei Dan

Publisher

IEEE

Cited by 35 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Interpretable Failure Localization for Microservice Systems Based on Graph Autoencoder;ACM Transactions on Software Engineering and Methodology;2024-09-13

2. An Intelligent Model of Anomaly Detection and Anomaly Localization in Images Using Hybrid Heuristic Adaptive Multiscale Attention-Based DenseNet and Cascaded Variational Autoencoder;International Journal of Pattern Recognition and Artificial Intelligence;2024-08-09

3. Density Transformer for Unsupervised Time Series Anomaly Detection in Cloud Computing;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

4. Detecting Cloud Anomaly via Broad Network-Based Contrastive Autoencoder;IEEE Transactions on Network and Service Management;2024-06

5. Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective;Proceedings of the ACM Web Conference 2024;2024-05-13

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