Temporal-Frequency Masked Autoencoders for Time Series Anomaly Detection-Reference-Cited by-同舟云学术

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Temporal-Frequency Masked Autoencoders for Time Series Anomaly Detection

Published:2024-05-13 Issue: Volume:54 Page:1228-1241
ISSN:
Container-title:2024 IEEE 40th International Conference on Data Engineering (ICDE)
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Author:

Fang Yuchen¹,Xie Jiandong²,Zhao Yan³,Chen Lu⁴,Gao Yunjun⁴,Zheng Kai⁵

Affiliation:

1. University of Electronic Science and Technology of China,China

2. Huawei Cloud Database Innovation Lab,China

3. Aalborg University,Denmark

4. Zhejiang University,China

5. Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China,Shenzhen,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10597630/10597390/10597757.pdf?arnumber=10597757

Reference65 articles.

1. FluxEV: A Fast and Effective Unsupervised Framework for Time-Series Anomaly Detection

2. Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud Detection

3. Autoencoder-based deep metric learning for network intrusion detection

4. Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives

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