Graph Laplacian Eigenvalues Empowered VAEs: A Novel Approach to Adaptive Latent Dimension Choice

Anomaly detection in multivariate time series (MTS) data is crucial for identifying unusual behaviors or events that may indicate system failures, fraud, or other issues. In many real-world scenarios, labeled anomalies are scarce or non-existent, making unsupervised learning methods essential. Neura...

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書誌詳細

主要な著者:	M. K. Saravana, M. S. Roopa, J. S. Arunalatha, K. R. Venugopal
フォーマット:	Artigo
言語:	Inglês
出版事項:	IEEE 2024-01-01
シリーズ:	IEEE Access
主題:	MTS Analysis Deep Learning MTS anomaly detection Variational Autoencoders (VAE) Latent Dimension Graph Laplacian Eigenvalues (GLE)
オンライン･アクセス:	https://ieeexplore.ieee.org/document/10680505/
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