233 citations · 259 across the 5 of their papers we have counts for
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cs.LG2023★ 233 cited
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial
Venkat Nemani, Luca Biggio, Xun Huan +6
On top of machine learning models, uncertainty quantification (UQ) functions as an essential layer of safety assurance that could lead to more principled decision making by enablin…
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…
cs.LG2022★ 7 cited
A Comprehensive Review of Digital Twin -- Part 2: Roles of Uncertainty Quantification and Optimization, a Battery Digital Twin, and Perspectives
Adam Thelen, Xiaoge Zhang, Olga Fink +7
As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, he…