Designs of graph echo state networks for node classification

Alessio Micheli, Domenico Tortorella

Abstract: Highlights•First systematic analysis of reservoir computing designs for node classification.•Proposing a set of topology-aware and -agnostic richness measures for node embeddings.•Random ensembles and dense orthogonal reservoirs perform generally better.•Extremely sparse reservoirs preserve accuracy and node embedding quality.