Phytophthora root and stem rot in soybeans results in substantial economic losses worldwide. In this study, a machine learning model based on a heterogeneous interaction graph attention network model ...

The network comprises a temporal graph convolutional network (TGCN) and a learnable adjacency matrix that enables us to utilize correlations between appliances and quantify their relationships.

The designed dynamic graph attention convolutional network uses electrode channel positions as prior knowledge to construct a graph update layer, ensuring the retention of important nodes during the ...

In this letter, we propose a visibility graph (VG)-based adjacency matrix representation of LS in conjunction with a residual deep neural network (ResNet) for accurate detection of COPD, namely, the ...

Learning curves showing the results of training and test loss per epoch for (A) the proposed graph convolutional network model with the airway adjacency matrix and (B) the multilayer perceptron model.

With artificial neural networks becoming more popular and capable, GNNs have become a powerful tool for many important applications.