I. Introduction
Graphs often occur as “natural” representations of structured objects in different application areas of machine learning. To adopt methods like central clustering or principal component analysis for graphs, an understanding of the structural version of the sample mean is imperative. But the concept of sample mean of graphs is hardly investigated, although a number of central clustering algorithms for graphs have been devised [1]–[3].