6 citations · 6 across the 3 of their papers we have counts for
4 papers
Stable network inference in high-dimensional graphical model using single-linkage
Emilie Devijver, Rémi Molinier, Mélina Gallopin
Stability, akin to reproducibility, is crucial in statistical analysis. This paper examines the stability of sparse network inference in high-dimensional graphical models, where se…
A comprehensive guideline for regularization-path variable selection in high-dimensional Gaussian linear regression
Perrine Lacroix, Mélina Gallopin, Marie-Laure Martin
This paper provides a comprehensive comparison of complete regularization-path-based variable selection procedures in high-dimensional Gaussian linear regression. Our simulation st…
Nonlinear network-based quantitative trait prediction from transcriptomic data
Emilie Devijver, Mélina Gallopin, Emeline Perthame
Quantitatively predicting phenotype variables by the expression changes in a set of candidate genes is of great interest in molecular biology but it is also a challenging task for…
Block-diagonal covariance selection for high-dimensional Gaussian graphical models
Emilie Devijver, Mélina Gallopin
Gaussian graphical models are widely utilized to infer and visualize networks of dependencies between continuous variables. However, inferring the graph is difficult when the sampl…