摘要 Training deep neural networks(训练深度神经网络) requires(需要) significant computational resources(大量计算资源) and large datasets(大型数据集) that are often confidential(机密的) or expensive(昂贵的) to collect. As a resul
摘要 Many real-world data(真实世界的数据) come in the form of graphs(以图片的形式). Graph neural networks (GNNs 图神经网络), a new family of machine learning (ML) models, have been proposed to fully leverage graph data(