3 papers
math.ST2026
Beyond Degree: Rooted Motif Signatures for Latent Position Identifiability in Graphon Models
Roland Boniface Sogan, Tabea Rebafka
Graphon estimation requires structural assumptions to address its intrinsic non-identifiability. A standard approach is degree-based identifiability, where the degree function is a…
stat.ME2026
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…
stat.ME2026
Low-Complexity and Consistent Graphon Estimation from Multiple Networks
Roland Boniface Sogan, Tabea Rebafka
Recovering the random graph model from an observed collection of networks is known to present significant challenges in the setting, where the networks do not share a common node s…