219 citations · 1.3k across the 47 of their papers we have counts for
47 papers
Co-clustering based exploratory analysis of mixed-type data tables
Aichetou Bouchareb, Marc Boullé, Fabrice Clérot +1
Co-clustering is a class of unsupervised data analysis techniques that extract the existing underlying dependency structure between the instances and variables of a data table as h…
Model Based Co-clustering of Mixed Numerical and Binary Data
Aichetou Bouchareb, Marc Boullé, Fabrice Clérot +1
Co-clustering is a data mining technique used to extract the underlying block structure between the rows and columns of a data matrix. Many approaches have been studied and have sh…
On the expressivity of bi-Lipschitz normalizing flows
Alexandre Verine, Benjamin Negrevergne, Fabrice Rossi +1
An invertible function is bi-Lipschitz if both the function and its inverse have bounded Lipschitz constants. Nowadays, most Normalizing Flows are bi-Lipschitz by design or by trai…
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…
Discovering Patterns in Time-Varying Graphs: A Triclustering Approach
Romain Guigourès, Marc Boullé, Fabrice Rossi
This paper introduces a novel technique to track structures in time varying graphs. The method uses a maximum a posteriori approach for adjusting a three-dimensional co-clustering…
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…