Abstract: Graph pooling technique as the essential component of graph neural networks has gotten increasing attention recently and it aims to learn graph-level representations for the whole graph.
A multivariate analysis of electroencephalography activity reveals super-additive enhancements to the neural encoding of audiovisual stimuli, providing new insights into how the brain integrates ...
Abstract: Graph convolutional neural networks (GCNs) have demonstrated effectiveness in processing graph structure. Due to the diversity and complexity of real-world graph data, heterogeneous GCN have ...
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