activity
20172026
most citedEfficient method for estimating the number of communities in a network

87 citations · 103 across the 8 of their papers we have counts for

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12 papers · 1 filter

cs.SI2025

Model inference for ranking from pairwise comparisons

Daniel Sánchez Catalina, George T. Cantwell

We consider the problem of ranking objects from noisy pairwise comparisons, for example, ranking tennis players from the outcomes of matches. We follow a standard approach to this…

cs.SI2025

Embedding networks with the random walk first return time distribution

Vedanta Thapar, Renaud Lambiotte, George T. Cantwell

We propose the first return time distribution (FRTD) of a random walk as an interpretable and mathematically grounded node embedding. The FRTD assigns a probability mass function t…

cs.SI2024★ 1 cited

An approximation for return time distributions of random walks on sparse networks

Erik Hormann, Renaud Lambiotte, George T. Cantwell

We propose an approximation for the first return time distribution of random walks on undirected networks. We combine a message-passing solution with a mean-field approximation, to…

cs.SI2020

The friendship paradox in real and model networks

George T. Cantwell, Alec Kirkley, M. E. J. Newman

The friendship paradox is the observation that the degrees of the neighbors of a node in any network will, on average, be greater than the degree of the node itself. In common parl…

cs.SI2020

Bayesian inference of network structure from unreliable data

Jean-Gabriel Young, George T. Cantwell, M. E. J. Newman

Most empirical studies of complex networks do not return direct, error-free measurements of network structure. Instead, they typically rely on indirect measurements that are often…

cs.SI2019

Inference for growing trees

George T. Cantwell, Guillaume St-Onge, Jean-Gabriel Young

One can often make inferences about a growing network from its current state alone. For example, it is generally possible to determine how a network changed over time or pick among…