Multilayer networks are a way to represent dependent connectivity patterns — e.g., time-dependence, multiple types of interactions, or both — that arise in many applications and which are difficult to incorporate into standard network representations. In the study of multilayer networks, it is important to investigate mesoscale (i.e., intermediate-scale) structures, such as communities, to discover features that lie between the microscale and the macroscale. We introduce a framework for the construction of generative models for mesoscale structure in multilayer networks. We model dependency at the level of partitions rather than with respect to edges, and treat the process of generating a multilayer partition separately from the process of generating edges for a given multilayer partition. Our framework can admit many features of empirical multilayer networks and explicitly incorporates a user-specified interlayer dependency structure. We discuss the parameters and some properties of our framework, and illustrate an example of its use with benchmark models for multilayer community-detection tools.
- Networks Seminar
For our popular Christmas lecture this year Chris Budd will give a seasonal talk with a number of light hearted applications of mathematics to the
Chris is currently Professor of Applied Mathematics at the University of Bath, and Professor of Geometry at Gresham College. He is a passionate populariser of mathematics and was awarded an OBE in 2015 for services to science and maths education.
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- Public Lecture