To address the above limitations, we propose an end-to-end framework, called Knowledge Graph Neural Network (KGN-N), to resolve the DDI prediction. Our frame-work can effectively …

KGNN: Knowledge Graph Neural Network for Drug-Drug Interaction Prediction. IJCAI' 20 accepted. Figure 1 shows the overview of KGNN. It takes the parsed DDI matrix and …

To address the above limitations, we propose an end-to-end framework, called Knowledge Graph Neural Network (KGNN), to resolve the DDI prediction. Our framework can effectively capture …

KGNV’s tower stands out. The broadcast studio is located in the white part of the barn just to the left of the tower. Since 1978, we have broadcast christian radio programs produced locally and …

To address the above limitations, we propose an end-to-end framework, called Knowledge Graph Neural Network (KGNN), to resolve the DDI prediction. Our framework can effectively capture …

为解决上述局限性，林轩等人提出了一种端到端的框架，即基于知识图谱的图神经网络（KGNN），以解决DDI预测问题。 该框架可通过在KG中挖掘相关联的关系，来有效地捕获 …

2022年5月21日 · We address the limitations by proposing the Kernel-based Graph Neural Network (KGNN). A KGNN consists of a GNN-based network as well as a kernel-based …

2019年5月11日 · Here we propose Knowledge-aware Graph Neural Networks with Label Smoothness regularization (KGNN-LS) to provide better recommendations. Conceptually, our …

2022年5月17日 · To address these issues, we develop a novel framework called KGNN to take full advantage of knowledge data for representation learning in the distributed learning system.

KGNN-LS applies the technique of graph neural networks (GNNs) to proces knowledge graphs for the purpose of recommendation. The model is enhanced by adding a label smoothness …