1 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 1 cited
An interpretable deep learning method for bearing fault diagnosis
Hao Lu, Austin M. Bray, Chao Hu +2
Deep learning (DL) has gained popularity in recent years as an effective tool for classifying the current health and predicting the future of industrial equipment. However, most DL…
cs.LG2023★ 1 cited
Federated Learning with Uncertainty-Based Client Clustering for Fleet-Wide Fault Diagnosis
Hao Lu, Adam Thelen, Olga Fink +2
Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring d…