Metrics in the space of high order proximity networks

This paper presents two families of distances in the space of high order proximity networks. The distances measure differences between networks and are shown to be valid metrics in the space of high order proximity networks modulo permutation isomorphisms. Practical implications are explored by comparing the coauthorship networks of two popular signal processing researchers. The metrics succeed in identifying their respective collaboration patterns.