Abstract: Graph neural networks (GNNs) have become the prevailing methodology for addressing graph data-related tasks, permeating critical domains like recommendation systems and drug development. The ...
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Abstract: To address the challenges of acoustic and vibration signals being susceptible to noise interference, coarse modality fusion, and static graph structures in industrial fault diagnosis, we ...
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