Daniel Schlr
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2026
Evaluating Tabular Representation Learning for Network Intrusion Detection
The paper systematically evaluates various tabular representation learning techniques to automatically extract robust features from NetFlow data for network intrusion detection, finding that supervised classification significantly outperforms unsupervised anomaly detection.
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