GCN is a multilayer connected neural network architecture and is ... integration module and the knowledge graph embedding module, and feed the fused features into the graph convolutional network ...

In this paper, a knowledge graph enhanced dynamic multi-graph convolutional network is proposed for traffic origin-destination forecasting, which integrates a knowledge graph embedding method ... by a ...

The advantage of using the language model-based feature vectors is that it does not require domain knowledge ... protein sequence embedding layer of the protein language pretrained model as the ...

This is based on the GNN message-passing architecture (Hamilton et al., 2017; Xu et al., 2018). During an embedding update ... In this paper, we proposed a graph convolutional neural network ...

Abstract: Knowledge ... a parameter-efficient embedding model that combines the benefits of a graph neural network (GNN) and a convolutional neural network (CNN) to solve the KBC task with OOKB ...