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math.ST2026
Adjacency Spectral Embeddings of Correlation Networks
Keith Levin
In many applications, weighted networks are constructed based on time series data: each time series is associated to a vertex and edge weights are given by pairwise correlations. T…
math.ST2026
Matching and mixing: Matchability of graphs under Markovian error
Zhirui Li, Keith D. Levin, Zhiang Zhao +1
We consider the problem of graph matching for a sequence of graphs generated under a time-dependent Markov chain noise model. Our edgelighter error model, a variant of the classica…
math.ST2026
On the Effect of Misspecifying the Embedding Dimension in Low-rank Network Models
Roddy Taing, Keith Levin
As network data has become ubiquitous in the sciences, there has been growing interest in network models whose structure is driven by latent node-level variables in a (typically lo…