6 papers
Generative hypergraph clustering: from blockmodels to modularity
Philip S. Chodrow, Nate Veldt, Austin R. Benson
Hypergraphs are a natural modeling paradigm for a wide range of complex relational systems. A standard analysis task is to identify clusters of closely related or densely interconn…
Annotated Hypergraphs: Models and Applications
Philip Chodrow, Andrew Mellor
Hypergraphs offer a natural modeling language for studying polyadic interactions between sets of entities. Many polyadic interactions are asymmetric, with nodes playing distinctive…
Moments of Uniform Random Multigraphs with Fixed Degree Sequences
Philip S. Chodrow
We study the expected adjacency matrix of a uniformly random multigraph with fixed degree sequence . This matrix arises in a variety of analyses of n…
Configuration Models of Random Hypergraphs
Philip S. Chodrow
Many empirical networks are intrinsically polyadic, with interactions occurring within groups of agents of arbitrary size. There are, however, few flexible null models that can sup…
Log-minor distributions and an application to estimating mean subsystem entropy
Alice C. Schwarze, Philip S. Chodrow, Mason A. Porter
A common task in physics, information theory, and other fields is the analysis of properties of subsystems of a given system. Given the covariance matrix of a system of cou…
Local Symmetry and Global Structure in Adaptive Voter Models
Philip S. Chodrow, Peter J. Mucha
Adaptive voter models (AVMs) are simple mechanistic systems that model the emergence of mesoscopic structure from local networked processes driven by conflict and homophily. AVMs d…