Variable-wise generative adversarial transformer in multivariate time series anomaly detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-023-05029-x.pdf
Reference54 articles.
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2. Liu S, Zhou B, Ding Q, Hooi B, Zhang Z, Shen H, Cheng X (2022) Time series anomaly detection with adversarial reconstruction networks. IEEE Trans Knowl Data Eng 35(4):4293–4306
3. Sharma DK, Dhankhar T, Agrawal G, Singh SK, Gupta D, Nebhen J, Razzak I (2021) Anomaly detection framework to prevent ddos attack in fog empowered iot networks. Ad Hoc Networks 121:102603. https://doi.org/10.1016/j.adhoc.2021.102603
4. Geiger A, Liu D, Alnegheimish S, Cuesta-Infante A, Veeramachaneni K (2020) Tadgan: time series anomaly detection using generative adversarial networks. In: 2020 IEEE international conference on big data (Big Data), IEEE, pp 33–43
5. Li D, Chen D, Jin B, Shi L, Goh J, Ng S-K (2019) Mad-gan: multivariate anomaly detection for time series data with generative adversarial networks. In: Artificial neural networks and machine learning–ICANN 2019: text and time series: 28th international conference on artificial neural networks, Munich, Germany, September 17–19, 2019, Proceedings, Part IV, Springer, pp 703–716
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