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Abstract: Heterogeneous Graph Neural Networks (HGNNs) are powerful tools for deep learning on heterogeneous graphs. Typical HGNNs require repetitive message passing during training, limiting ...
Abstract: Synthetic power graphs have recently been widely used to assist researchers in analyzing power grids as complex networks. In general, power graphs are sparsely connected, scale-free with ...
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