Compared with traditional neural networks, graph convolutional networks are very suitable for processing graph structured data. However, common graph convolutional network methods often have ...

Graph Convolutional Network-based Scheduler for Distributing Computation in the Internet of Robotic Things - ANRGUSC/gcnschedule-turtlenet. ... edGNN contains source code for solving inference ...

More information: Du Lei et al, Graph Convolutional Networks Reveal Network-Level Functional Dysconnectivity in Schizophrenia, Schizophrenia Bulletin (2022).DOI: 10.1093/schbul/sbac047 ...

Keywords: COVID-19, deep learning, graph convolutional network, predicting, public transportation. Citation: Anno S, Hirakawa T, Sugita S and Yasumoto S (2022) A graph convolutional network for ...

Keywords: EEG, driving fatigue detection, channel attention mechanism, graph convolutional network, spatial attention mechanism. Citation: Liu H, Liu Q, Cai M, Chen K, Ma L, Meng W, Zhou Z and Ai Q ...