28 citations · 38 across the 9 of their papers we have counts for
4 papers · 1 filter
A Bayesian framework with adaptive elastic nets for the inference of Gaussian graphical models
Roland B. Sogan, Tabea Rebafka, Fanny Villers
Estimating conditional independence graphs from high-dimensional Gaussian data is challenging because methods must detect relevant edges while rigorously controlling statistical er…
Enhancing the Power of Gaussian Graphical Model Inference by Modeling the Graph Structure
Valentin Kilian, Tabea Rebafka, Fanny Villers
For the problem of inferring a Gaussian graphical model (GGM), this work explores the application of a recent approach from the multiple testing literature for graph inference. The…
A semiparametric extension of the stochastic block model for longitudinal networks
Catherine Matias, Tabea Rebafka, Fanny Villers
To model recurrent interaction events in continuous time, an extension of the stochastic block model is proposed where every individual belongs to a latent group and interactions b…
On least favorable configurations for step-up-down tests
Gilles Blanchard, Thorsten Dickhaus, Etienne Roquain +1
This paper investigates an open issue related to false discovery rate (FDR) control of step-up-down (SUD) multiple testing procedures. It has been established in earlier literature…