François Caron (University of Oxford)

A Bayesian nonparametric model for undirected and multi-edges networks

In this talk, I will present ongoing work on a Bayesian nonparametric specification for either undirected or multi-edge directed networks, building on the framework of completely random measures. The formulation allows for an unbounded number of nodes in the network, while encouraging a sparse set of interactions. Importantly, as demonstrated empirically, the model captures salient features of real world networks like power-law degree distributions with possible exponential cut-off in the tails. These properties, in addition to sparsity, are determined by three hyperparameters. I will also discuss an approach for scaling computations to large networks.
This is joint work with Emily Fox (University of Washington).