Ian Gallagher
Ian Gallagher
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A simple and powerful framework for stable dynamic network embedding
In this paper, we address the problem of dynamic network embedding, that is, representing the nodes of a dynamic network as evolving …
Ed Davis
,
Ian Gallagher
,
Daniel Lawson
,
Patrick Rubin-Delanchy
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Intensity profile projection: a framework for continuous-time representation learning for dynamic networks
We present a new algorithmic framework, Intensity Profile Projection, for learning continuous-time representations of the nodes of a …
Alex Modell
,
Ian Gallagher
,
Emma Ceccherini
,
Nick Whiteley
,
Patrick Rubin-Delanchy
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Spectral embedding of weighted graphs
This paper concerns the statistical analysis of a weighted graph through spectral embedding. Under a latent position model in which the …
Ian Gallagher
,
Andrew Jones
,
Anna Bertiger
,
Carey Priebe
,
Patrick Rubin-Delanchy
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Spectral embedding and the latent geometry of multipartite networks
Spectral embedding finds vector representations of the nodes of a network, based on the eigenvectors of its adjacency or Laplacian …
Alex Modell
,
Ian Gallagher
,
Joshua Cape
,
Patrick Rubin-Delanchy
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Spectral embedding for dynamic networks with stability guarantees
We consider the problem of embedding a dynamic network, to obtain time-evolving vector representations of each node, which can then be …
Ian Gallagher
,
Andrew Jones
,
Patrick Rubin-Delanchy
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Persistent homology of graph embeddings
Popular network models such as the mixed membership and standard stochastic block model are known to exhibit distinct geometric …
Vinesh Solanki
,
Patrick Rubin-Delanchy
,
Ian Gallagher
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