Abstract: Robust and accurate traffic forecasting is a key issue in intelligent transportation systems. Existing studies usually employ pre-defined spatial graph or learned fixed adjacency graph and ...
Abstract: Graph Convolution Networks (GCNs) have achieved remarkable success in representation of structured graph data. As we know that traditional GCNs are generally defined on the fixed first-order ...
Mental disorders are among the most widespread diseases globally. In this work, we propose a novel framework called $\textbf{NuroTree}$ that contributes to computational neuroscience by integrating ...
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