A UDA framework with multi-scale input mixing and Dirichlet-prior uncertainty estimation improves F1 and calibration on five time-series benchmarks.
Condition monitoring of bearing damage in electromechanical drive systems by using motor current signals of electric motors: A benchmark data set 16 for data-driven classification,
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Uncertainty Awareness on Unsupervised Domain Adaptation for Time Series Data
A UDA framework with multi-scale input mixing and Dirichlet-prior uncertainty estimation improves F1 and calibration on five time-series benchmarks.