85 citations
- Centre National de la Recherche ScientifiqueFR9 papers
- CEA GrenobleFR7 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR7 papers
- Université Grenoble AlpesFR5 papers
- Université Joseph FourierFR4 papers
- Adventist Health Simi ValleyUS3 papers
- Laboratoire des Sciences pour la Conception, l'Optimisation et la ProductionFR3 papers
- Laboratoire Jean KuntzmannFR3 papers
- DM-STAT (United States)US2 papers
- Institut polytechnique de GrenobleFR2 papers
- Laboratoire de Chimie et Biologie des MétauxFR2 papers
- Leonard J. Chabert Medical CenterUS2 papers
25 papers
Spatial constraints improve filtering of measurement noise from animal tracks
Alexandre Delporte, Susanne Ditlevsen, Adeline Samson
Advances in tracking technologies for animal movement require new statistical tools to better exploit the increasing amount of data. Animal positions are usually calculated using t…
Benchmarking Brain Connectivity Graph Inference: A Novel Validation Approach
Alice Chevaux, Ali Fahkar, Kévin Polisano +2
Inferring a binary connectivity graph from resting-state fMRI data for a single subject requires making several methodological choices and assumptions that can significantly affect…
Disentangling Modes and Interference in the Spectrogram of Multicomponent Signals
Kévin Polisano, Sylvain Meignen, Nils Laurent +1
In this paper, we investigate how the spectrogram of multicomponent signals can be decomposed into a mode part and an interference part. We explore two approaches: (i) a variationa…
G{é}n{é}ration de Matrices de Corr{é}lation avec des Structures de Graphe par Optimisation Convexe
Ali Fahkar, Kévin Polisano, Irène Gannaz +1
This work deals with the generation of theoretical correlation matrices with specific sparsity patterns, associated to graph structures. We present a novel approach based on convex…
Generating Correlation Matrices with Graph Structures Using Convex Optimization
Ali Fakhar, Kévin Polisano, Irène Gannaz +1
This work deals with the generation of theoretical correlation matrices with specific sparsity patterns, associated to graph structures. We present a novel approach based on convex…
Community detection for binary graphical models in high dimension
Julien Chevallier, Guilherme Ost
Let components be partitioned into two communities, denoted and , possibly of different sizes. Assume that they are connected via a directed and weight…