A Statistical Interpretation of Spectral Embedding: The Generalised Random Dot Product Graph
谱嵌入的统计解释：广义随机点积图
Abstract Spectral embedding is a procedure which can be used to obtain vector representations of the nodes of a graph. This paper proposes a generalisation of the latent position network model known as the random dot product graph, to allow interpretation of those vector representations as latent position estimates. The generalisation is needed to model heterophilic connectivity (e.g. ‘opposites attract’) and to cope with negative eigenvalues more generally. We show that,…