5 papers
Note on edge expansion and modularity in preferential attachment graphs
Colin McDiarmid, Katarzyna Rybarczyk, Fiona Skerman +1
Edge expansion is a parameter indicating how well-connected a graph is. It is useful for designing robust networks, analysing random walks or information flow through a network and…
Modularity and random graphs
Colin McDiarmid, Fiona Skerman
This work will appear as a chapter in a forthcoming volume titled `Topics in Probabilistic Graph Theory'. For a given graph , each partition of the vertices has a modularity sco…
Is it easier to count communities than find them?
Cynthia Rush, Fiona Skerman, Alexander S. Wein +1
Random graph models with community structure have been studied extensively in the literature. For both the problems of detecting and recovering community structure, an interesting…
From flip processes to dynamical systems on graphons
Frederik Garbe, Jan Hladký, Matas Šileikis +1
We introduce a class of random graph processes, which we call flip processes. Each such process is given by a rule which is a function $\mathcal{R}:\mathcal{H}_k\rightarrow \mathca…
Logical limit laws for Mallows random permutations
Tobias Muller, Fiona Skerman, Teun W. Verstraaten
A random permutation of follows the $\DeclareMathOperator{\Mallows}{Mallows}\Mallows(n,q)$ distribution with parameter if is…