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arXiv Machine Learning By Lucas Gouveia Omena Lopes, Thales Miranda de Almeida Vieira, Eduardo Toledo de Lima Junior, William Wagner Matos Lira

An Explainable LLM Agent Layer for Open-World Anomaly Detection in Oil Wells

Read the original on arXiv Machine Learning →

arXiv:2608. 04041v1 Announce Type: new Abstract: Open-World Learning (OWL) pipelines for oil well anomaly detection have recently been shown to combine autoencoder-based detection, multiclass classification, and Mahalanobis-based novelty detection on the public 3W dataset.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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