Publications

Optimization and Control

Unbalanced L1 optimal transport for vector valued measures and application to Full Waveform Inversion

Optimal transport has recently started to be successfully employed to define misfit or loss functions in inverse problems. However, it is a problem intrinsically defined for positive (probability) measures and therefore strategies are needed for its…

Gabriele Todeschi, Ludovic Métivier, Jean-Marie Mirebeau

Journal of Computational Physics - 2025

Life Sciences

Machine learning models for diagnosis and risk prediction in eating disorders, depression, and alcohol use disorder

This study uses machine learning models to uncover diagnostic and risk prediction markers for eating disorders (EDs), major depressive disorder (MDD), and alcohol use disorder (AUD). Utilizing case-control samples (ages 18-25 years) and a…

Sylvane Desrivières, Zuo Zhang, Lauren Robinson, Robert Whelan, Lee Jollans, Zijian Wang, Frauke Nees, Congying Chu, Marina Bobou, Dongping Du, Ilinca Cristea, Tobias Banaschewski, Gareth Barker, Arun Bokde, Antoine Grigis, Hugh Garavan, Andreas Heinz, Rudiger Bruhl, Jean-Luc Martinot, Marie-Laure Paillère Martinot, Eric Artiges, Dimitri Papadopoulos Orfanos, Luise Poustka, Sarah Hohmann, Sabina Millenet, Juliane Fröhner, Michael Smolka, Nilakshi Vaidya, Henrik Walter, Jeanne Winterer, M. Broulidakis, Betteke van Noort, Argyris Stringaris, Jani Penttilä, Yvonne Grimmer, Corinna Insensee, Andreas Becker, Yuning Zhang, Sinead King, Julia Sinclair, Gunter Schumann, Ulrike Schmidt, Dimitri Papadopoulos Orfanos, Betteke van Noort

Journal of Affective Disorders - 2025

Other Statistics

Stein Boltzmann Sampling: A Variational Approach for Global Optimization

In this paper, we present a flow-based method for global optimization of continuous Sobolev functions, called Stein Boltzmann Sampling (SBS). SBS initializes uniformly a number of particles representing candidate solutions, then uses the Stein…

Gaëtan Serré, Argyris Kalogeratos, Nicolas Vayatis

Analysis of PDEs

Microlocal Partition of Energy for Fractional-Type Dispersive Equations

This paper is devoted to the proof of microlocal partition of energy for fractional-type dispersive equations including Schrödinger equation, linearized gravity or capillary water-wave equation and half-Klein-Gordon equation. Roughly speaking, a…

Haocheng Yang

Analysis & PDE - 2025

Mathematics

The anisotropy of 2D or 3D Gaussian random fields through their Lipschitz-Killing curvature densities

We are interested here in modeling and estimating the anisotropy of 2D and 3D Gaussian random fields through the geometry of their excursion sets. In order to do this, we use Lipschitz-Killing curvatures of the level sets as functions of the levels…

Hermine Biermé, Agnès Desolneux

The Annals of Applied Probability - 2025

Numerical Analysis

Monotone discretization of anisotropic differential operators using Voronoi's first reduction

We consider monotone discretization schemes, using adaptive finite differences on Cartesian grids, of partial differential operators depending on a strongly anisotropic symmetric positive definite matrix. For concreteness, we focus on a linear…

Joseph Frédéric Bonnans, Guillaume Bonnet, Jean-Marie Mirebeau

Constructive Approximation - 2025

Cancer

Phenotypic and epigenetic heterogeneity in FGFR2 ‐fused glial and glioneuronal tumours

Aims: FGFR-fused central nervous system (CNS) tumours are rare and are usually within the glioneuronal and neuronal tumours or the paediatric-type diffuse low-grade glioma spectrum. Among this spectrum, FGFR2 fusion has been documented in tumours…

Alice Métais, Volodia Dangouloff-Ros, Jeremy Garcia, Quentin Vannod-Michel, Marie Csanyi, Arnault Tauziède-Espariat, Romain Appay, Claude‐alain Maurage, Emmanuelle Uro-Coste, David Meyronet, Valérie Rigau, Audrey Rousseau, Guillaume Chotard, Jocelyne Hamelin, Gaelle Pierron, Carole Colin, Morgan Ollivier, Margaux Roques, Corentin Provost, Jean‐philippe Cottier, Johan Pallud, Fabrice Chrétien, Lelio Guida, Thomas Blauwblomme, Nathalie Boddaert, Pascale Varlet, Myriam Edjlali, Dominique Figarella-Branger, Jean-Marc Constans

Neuropathology and Applied Neurobiology - 2024

Life Sciences

Reappraisal of prognostic factors in CNS WHO grade 3 oligodendrogliomas IDH-mutant and 1p/19q co-deleted: Lessons from the French POLA cohort

Background In the POLA cohort, 3 pathological groups of CNS WHO grade 3 oligodendroglioma IDH-mutant and 1p/19q co-deleted have been described: group 1 (high mitotic count only), group 2 (microvascular proliferation MVP and no necrosis), and group 3…

Domique Figarella-Branger, Domique Figarella-Branger, Carole Colin, Karima Mokhtari, Emmanuelle Uro-Coste, Emmanuelle Uro-Coste, Ahmed Idbaih, Romain Appay, Emeline Tabouret, Mehdi Touat, Antoine Seyve, Catherine Carpentier, Caroline Dehais, Caroline Dehais, François Ducray, François Ducray, C Desenclos, N Guillain, P Menei, A Rousseau, T Cruel, S Lopez, M Abad, N Hamdan, C Adam, F Parker, R Seizeur, I Quintin-Roué, G Chotard, C Bronnimann, D Ricard, C Godfraind, T Khallil, D Cazals-Hatem, T Faillot, C Gaultier, Mc Tortel, I Carpiuc, P Richard, H Aubriot-Lorton, F Ghiringhelli, A Djelad, Ca Maurage, Em Gueye, F Labrousse, D Meyronet, O Chinot, L Bauchet, V Rigau, G Gauchotte, L Taillandier, M Campone, D Loussouarn, V Bourg, F Vandenbos-Burel, J-S Guillamo, P Roger, C Blechet, H Adle-Biassette, F Bielle, A Carpentier, S Milin, M Wager, P Colin, Md Diebold, D Chiforeanu, E Vauleon, F Marguet, O Langlois, F Forest, Mj Motso-Fotso, M Andraud, M Khettab, B Lhermitte, G Noel, M Bernier, N Younan, C Rousselot-Denis, I Zemmoura, C Joubert, E Cohen-Moyal, F Dhermain

Neuro-Oncology - 2024

Computer Vision and Pattern Recognition

Feeding CNNs with domain knowledge

In the Oil & Gas industry, increasing production, recovery rates, and the lifespan of oil fields constitutes a major technological challenge. Borehole imaging tools, which provide high-resolution images of the borehole wall based on physical…

Ahmed Ben Saad

Statistics Theory

Geodesic slice sampling on Riemannian manifolds

We propose a theoretically justified and practically applicable slice sampling based Markov chain Monte Carlo (MCMC) method for approximate sampling from probability measures on Riemannian manifolds. The latter naturally arise as posterior…

Alain Durmus, Samuel Gruffaz