25 citations · 40 across the 5 of their papers we have counts for
5 papers
Bridging Maximum Likelihood and Optimal Transport for Efficient Inference and Model Selection in Stochastic Block Models
Simon Queric, Cédric Vincent-Cuaz, Charles Bouveyron +1
We study inference in stochastic block models (SBMs) through the lens of optimal transport (OT). We first establish that maximum likelihood variational inference (MLVI) can be inte…
Block modelling in dynamic networks with non-homogeneous Poisson processes and exact ICL
Marco Corneli, Pierre Latouche, Fabrice Rossi
We develop a model in which interactions between nodes of a dynamic network are counted by non homogeneous Poisson processes. In a block modelling perspective, nodes belong to hidd…
Exact ICL maximization in a non-stationary temporal extension of the stochastic block model for dynamic networks
Marco Corneli, Pierre Latouche, Fabrice Rossi
The stochastic block model (SBM) is a flexible probabilistic tool that can be used to model interactions between clusters of nodes in a network. However, it does not account for in…
Modelling time evolving interactions in networks through a non stationary extension of stochastic block models
Marco Corneli, Pierre Latouche, Fabrice Rossi
In this paper, we focus on the stochastic block model (SBM),a probabilistic tool describing interactions between nodes of a network using latent clusters. The SBM assumes that the…
Exact ICL maximization in a non-stationary time extension of the latent block model for dynamic networks
Marco Corneli, Pierre Latouche, Fabrice Rossi
The latent block model (LBM) is a flexible probabilistic tool to describe interactions between node sets in bipartite networks, but it does not account for interactions of time var…