KerGNNs: Interpretable Graph Neural Networks with Graph Kernels
KerGNNs: Interpretable Graph Neural Networks with Graph Kernels
Graph kernels are historically the most widely-used technique for graph classification tasks. However, these methods suffer from limited performance because of the hand-crafted combinatorial features of graphs. In recent years, graph neural networks (GNNs) have become the state-of-the-art method in downstream graph-related tasks due to their superior performance. Most GNNs …