Graph Neural Networks, Transformers, Machine Learning, Artificial Intelligence, Graph Processing.
graph kernels. The proposed GKATs were inspired by recent research on dense linear attention transformers, where studies have shown that kernel-based approaches are very effective over sparse attention layers. Following this path, GKATs model graph attention within each layer as a Hadamard product