221 citations · 434 across the 31 of their papers we have counts for
6 papers · 1 filter
Goodness of fit of logistic models for random graphs
Pierre Latouche, Stéphane Robin, Sarah Ouadah
Logistic regression is a natural and simple tool to understand how covariates contribute to explain the topology of a binary network. Once the model fitted, the practitioner is int…
Detection of adaptive shifts on phylogenies using shifted stochastic processes on a tree
Paul Bastide, Mahendra Mariadassou, Stéphane Robin
Comparative and evolutive ecologists are interested in the distribution of quantitative traits among related species. The classical framework for these distributions consists of a…
Degree-based goodness-of-fit tests for heterogeneous random graph models : independent and exchangeable cases
Sarah Ouadah, Stéphane Robin, Pierre Latouche
The degrees are a classical and relevant way to study the topology of a network. They can be used to assess the goodness-of-fit for a given random graph model. In this paper we int…
Exact and approximate inference in graphical models: variable elimination and beyond
Nathalie Peyrard, Marie-Josée Cros, Simon de Givry +5
Probabilistic graphical models offer a powerful framework to account for the dependence structure between variables, which is represented as a graph. However, the dependence betwee…
A factor model approach for the joint segmentation with between-series correlation
Xavier Collilieux, Emilie Lebarbier, Stéphane Robin
We consider the segmentation of set of correlated time-series, the correlation being allowed to take an arbitrary form but being the same at each time-position. We show that encodi…
A closed-form approach to Bayesian inference in tree-structured graphical models
Loïc Schwaller, Stéphane Robin, Michael Stumpf
We consider the inference of the structure of an undirected graphical model in an exact Bayesian framework. More specifically we aim at achieving the inference with close-form post…