arXiv Machine Learning June 19, 2026 By Reza Jalayer, Masoud Jalayer, Andrea Mor, Carlotta Orsenigo, Carlo Vercellis

Evaluating deep learning models for fault diagnosis of a rotating machinery with epistemic and aleatoric uncertainty

Read the original on arXiv Machine Learning →

arXiv:2412. 18980v2 Announce Type: replace Abstract: Uncertainty-aware deep learning (DL) models recently gained attention in fault diagnosis as a way to promote the reliable detection of faults when out-of-distribution (OOD) data arise from unseen faults (epistemic uncertainty) or the presence of noise (aleatoric uncertainty).

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