Graph Neural Networks, Transformers, Machine Learning, Artificial Intelligence, Graph Processing.
layers scale linear time & memory, not requiring explicitly storing graph representations (such as adjacency matrices) to compute attention layers if a graph kernel has finite (at least on expectation) (random) feature representation. GKATs are highly flexible since they can be used with various