165 citations · 177 across the 2 of their papers we have counts for
5 papers
Spectral clustering under degree heterogeneity: a case for the random walk Laplacian
Alexander Modell, Patrick Rubin-Delanchy
This paper shows that graph spectral embedding using the random walk Laplacian produces vector representations which are completely corrected for node degree. Under a generalised r…
The multilayer random dot product graph
Andrew Jones, Patrick Rubin-Delanchy
We present a comprehensive extension of the latent position network model known as the random dot product graph to accommodate multiple graphs -- both undirected and directed -- wh…
Manifold structure in graph embeddings
Patrick Rubin-Delanchy
Statistical analysis of a graph often starts with embedding, the process of representing its nodes as points in space. How to choose the embedding dimension is a nuanced decision i…
Choosing Between Methods of Combining p-values
Nicholas Heard, Patrick Rubin-Delanchy
Combining p-values from independent statistical tests is a popular approach to meta-analysis, particularly when the data underlying the tests are either no longer available or are…
Consistency of adjacency spectral embedding for the mixed membership stochastic blockmodel
Patrick Rubin-Delanchy, Carey E. Priebe, Minh Tang
The mixed membership stochastic blockmodel is a statistical model for a graph, which extends the stochastic blockmodel by allowing every node to randomly choose a different communi…