🔹 From Simple Graphs to Real-World Networks Graphs are one of the most powerful tools in science and data modeling. They help us represent relationships — whether between atoms, cities, or people. A ...

Abstract: Graph Convolution Networks (GCNs) have achieved remarkable success in representation of structured graph data. As we know that traditional GCNs are generally defined on the fixed first-order ...

Medical applications of mathematical modeling, including machine learning models, knowledge graphs, and health digital twins, primarily involve the prediction of patient outcomes. This expert ...