FIGURE 1. Framework of the proposed GGSC model. (A) Two drug–side effect heterogeneous graphs constructed based on two kinds of drug similarities. (B) Enhanced topological representation learning via ...

Graph Auto-Encoders (GAEs) are end-to-end trainable neural network models for unsupervised learning, clustering and link prediction on graphs. GAEs are based on Graph Convolutional Networks (GCNs), a ...

However, the application of this information in 2D-to-3D pose estimation remains underdeveloped. To address this issue, we propose the TMGCTE (Two-step Mixed Graph Convolution Transformer Encoder) ...

Pinterest today shared details about how it created PinSage, a graph convolutional network that can learn about things like nearby Pins, or nodes, in massive web-scale graphs. Pinterest began to ...