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 ...
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 ...
Abstract: Human motion prediction aims to forecast future motions based on historical motion sequences. Graph Convolutional Networks (GCNs) are widely used in this field. However, the high ...