ESN-DAGMM adapts DAGMM with an ESN layer for temporal modeling and reports 269.59% better average clustering quality than baselines on 10% of an O-RAN video-streaming dataset.
Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection,
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ESN-DAGMM: A Lightweight Framework for Unsupervised Time-Series Data Monitoring in 5G O-RAN Networks
ESN-DAGMM adapts DAGMM with an ESN layer for temporal modeling and reports 269.59% better average clustering quality than baselines on 10% of an O-RAN video-streaming dataset.