165 citations · 244 across the 23 of their papers we have counts for
3 papers · 1 filter
Implications of sparsity and high triangle density for graph representation learning
Hannah Sansford, Alexander Modell, Nick Whiteley +1
Recent work has shown that sparse graphs containing many triangles cannot be reproduced using a finite-dimensional representation of the nodes, in which link probabilities are inne…
Statistical exploration of the Manifold Hypothesis
Nick Whiteley, Annie Gray, Patrick Rubin-Delanchy
The Manifold Hypothesis is a widely accepted tenet of Machine Learning which asserts that nominally high-dimensional data are in fact concentrated near a low-dimensional manifold,…
Spectral embedding and the latent geometry of multipartite networks
Alexander Modell, Ian Gallagher, Joshua Cape +1
Spectral embedding finds vector representations of the nodes of a network, based on the eigenvectors of a properly constructed matrix, and has found applications throughout science…