The complete multipartite graph and the complete multi-layered graph are both generalizations of the complete bipartite graph. These two kinds of graphs have recursive structure and offer a very ...

This study aims to address these limitations by developing a novel graph-based deep learning model that fully utilizes both functional and structural information from multi-frequency EEG data. Methods ...

Most existing methods for predicting drug-drug interactions (DDI) predominantly concentrate on capturing the explicit relationships among drugs, overlooking the valuable implicit correlations present ...

To address these challenges, we propose a line parameter identification method based on Graph Attention Networks and Multi-gate Mixture-of-Experts. The topological structure of the power grid and the ...

Despite the fact that graph databases have known efficiency advantages over relational databases for dealing with geospatial, temporal, and social network data, simply using a graph database is not ...