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 ...
DataCamp is geared towards data science and analytics, offering specialized Python tracks with practical exercises using ...
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 ...
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