Graphs, visual representations outlining the relationships between different entities, concepts or variables, can be very ...

This article proposes a fault diagnosis algorithm based on ambient signals and graph convolutional networks (GCNs), approaching from two perspectives, broadening the input information sources and ...

torch==1.9.0 tqdm==4.61.2 torch_scatter==2.0.7 torch_geometric==2.0.2 torch_sparse==0.6.10 pandas==1.1.5 matplotlib==3.3.4 scipy==1.5.4 numpy==1.16.2 loguru==0.5.3 scikit-learn==1.0.1 ...

Currently, our Graph Schema defaults to a simple template. However, new users are often unfamiliar with graphs, making schema construction challenging. We can simplify this process (semi-automatically ...

Traditional data mining techniques, such as SVM and KNN, are not suitable for such small sample data, while Graph Convolutional Neural Network (GCN)model has a high accuracy for small sample data.