Search Results for author: Stéphane Robin

Found 7 papers, 1 papers with code

Motif-based tests for bipartite networks

no code implementations27 Jan 2021 Sarah Ouadah, Pierre Latouche, Stéphane Robin

Based on these results, we define a goodness-of-fit test for the B-EDD model and propose a family of tests for network comparisons.

Statistics Theory Statistics Theory

Accounting for missing actors in interaction network inference from abundance data

1 code implementation28 Jul 2020 Raphaëlle Momal, Stéphane Robin, Christophe Ambroise

Network inference aims at unraveling the dependency structure relating jointly observed variables.

Applications Computation

Variational inference for sparse network reconstruction from count data

no code implementations8 Jun 2018 Julien Chiquet, Mahendra Mariadassou, Stéphane Robin

We adopt a different stance by relying on a latent model where we directly model counts by means of Poisson distributions that are conditional to latent (hidden) Gaussian correlated variables.


Variational inference for probabilistic Poisson PCA

no code implementations20 Mar 2017 Julien Chiquet, Mahendra Mariadassou, Stéphane Robin

A typical example is the joint observation of the respective abundances of a set of species in a series of sites, aiming to understand the co-variations between these species.


Exact Bayesian inference for off-line change-point detection in tree-structured graphical models

no code implementations25 Mar 2016 Loïc Schwaller, Stéphane Robin

The multivariate distribution of the observations is supposed to follow a graphical model, whose graph and parameters are affected by abrupt changes throughout time.

Bayesian Inference Change Point Detection +2

Exact and approximate inference in graphical models: variable elimination and beyond

no code implementations29 Jun 2015 Nathalie Peyrard, Marie-Josée Cros, Simon de Givry, Alain Franc, Stéphane Robin, Régis Sabbadin, Thomas Schiex, Matthieu Vignes

We illustrate the techniques reviewed in this article on benchmarks of inference problems in genetic linkage analysis and computer vision, as well as on hidden variables restoration in coupled Hidden Markov Models.

Cannot find the paper you are looking for? You can Submit a new open access paper.