activity
20242026
most citedDetecting local perturbations of networks in a latent hyperbolic embedding space

10 citations · 16 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.NC2026

Graph-based analysis of inflammatory profiles in New Onset Refractory Status Epilepticus (NORSE)

Linon Denis, Martin Guillemaud, Vincent Navarro +2

Background and Objectives: Cryptogenic new-onset refractory status epilepticus (cNORSE) represents one of the most severe forms of status epilepticus, occurring in patients without…

cs.SI2025

Hyperbolic embedding of multilayer networks

Martin Guillemaud, Vera Dinkelacker, Mario Chavez

Multilayer networks offer a powerful framework for modeling complex systems across diverse domains, effectively capturing multiple types of connections and interdependent subsystem…

q-bio.NC2024★ 2 cited

Geometric representations of brain networks can predict the surgery outcome in temporal lobe epilepsy

Martin Guillemaud, Alice Longhena, Louis Cousyn +4

Epilepsy surgery, particularly for temporal lobe epilepsy (TLE), remains a vital treatment option for patients with drug-resistant seizures. However, accurately predicting surgical…

q-bio.NC2024★ 4 cited

Hyperbolic embedding of brain networks detects regions disrupted by neurodegeneration in Alzheimer's disease

Alice Longhena, Martin Guillemaud, Fabrizio De Vico Fallani +2

Graph theoretical methods have proven valuable for investigating alterations in both anatomical and functional brain connectivity networks during Alzheimer's disease (AD). Recent s…

q-bio.QM2024★ 10 cited

Detecting local perturbations of networks in a latent hyperbolic embedding space

Alice Longhena, Martin Guillemaud, Mario Chavez

Graph theoretical approaches have been proven to be effective in the characterization of connected systems, as well as in quantifying their dysfunction due to perturbation. In this…