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Fault Detection and Diagnosis with Imbalanced and Noisy Data: A Hybrid Framework for Rotating Machinery

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Fault Detection and Diagnosis with Imbalanced and Noisy Data: A Hybrid Framework for Rotating Machinery

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Deep Learning Generalization with Limited and Noisy Labels

A Methodology for Evaluating the Robustness of Anomaly Detectors to Adversarial Attacks in Industrial Scenarios

Graph Neural Networks With Lifting-Based Adaptive Graph Wavelets

Lightweight HI source finding for next generation radio surveys

A Machine Learning-based Framework for Forecasting Sales of New Products With Short Life Cycles Using Deep Neural Networks

Single-Trace Clustering Power Analysis of the Point-Swapping Procedure in the Three Point Ladder of Cortex-M4 SIKE

Determining 1D fast-ion velocity distribution functions from ion cyclotron emission data using deep neural networks

On Vacuous and Non-Vacuous Generalization Bounds for Deep Neural Networks.

Systematic analysis of wavelet denoising methods for neural signal processing

AL2: Progressive Activation Loss for Learning General Representations in Classification Neural Networks