Multivariate Time Series Anomaly Detection Using Directed Hypergraph Neural Networks
Multivariate time series anomaly detection is a challenging problem because there can be a number of complex relationships between variables in multivariate time series. Although graph neural networks have been shown to be effective in capturing variable-variable relationships (i.e. relationships be...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Applied Artificial Intelligence |
| Online Access: | https://www.tandfonline.com/doi/10.1080/08839514.2025.2538519 |
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