Abstract: Graph Convolutional Neural Networks (graph CNNs) have been widely used for graph data representation and semi-supervised learning tasks. However, existing graph CNNs generally use a fixed ...
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Abstract: We propose a Multi-graph Attention spatial-temporal graph convolutional network (MGA-STGCN) for AHP risk forecasting. To describe the temporal and spatial features of the area, we use ...
It’s open-source and lightweight, and it’s minimalistic on the surface yet lets you build complex knowledge systems if you ...
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