5 citations
- Institut Universitaire de FranceFR11 papers
- Université de LorraineFR7 papers
- Institut Élie Cartan de LorraineFR6 papers
- Osiris Therapeutics (United States)US3 papers
- Département d'InformatiqueFR2 papers
- Laboratoire de Probabilités et Modèles AléatoiresFR2 papers
- Laboratoire de Probabilités, Statistique et ModélisationFR2 papers
- Leibniz Institute of Environmental MedicineDE2 papers
- Sierra Engineering (United States)US2 papers
- Université Paris-SaclayFR2 papers
- American Medical Informatics AssociationUS1 paper
- Centre de Mathématiques Appliquées de l'École polytechniqueFR1 paper
21 papers
Existence of solutions to the voltage-conductance kinetic equation in a general conductivity regime
C Fonte Sanchez, S Mischler, D Salort
We establish the existence of a weak solution to the Voltage-Conductance kinetic equation for any conductivity parameter and any reasonable initial datum, and in particular without…
Attention-based PCA
Rodrigo Maulen-Soto, Claire Boyer
We study attention mechanisms through the lens of a canonical unsupervised problem: principal component analysis (PCA). We show that, when trained on Gaussian data, both softmax an…
The -Trace System
Daniel Barlet
We study a simple 1-parameter perturbation of the regular holonomic Trace System satisfied by a complex power of the root of the universal polynomial of degree k as a holomorphic f…
Diachronic Stereo Matching for Multi-Date Satellite Imagery
Elías Masquil, Luca Savant Aira, Roger Marí +3
Recent advances in image-based satellite 3D reconstruction have progressed along two complementary directions. On one hand, multi-date approaches using NeRF or Gaussian-splatting j…
Modulating the tennis racket grip during motor imagery influences serve accuracy and performance: A pilot study
Aymeric Guillot, Julien Gauthier, Jeanne Lejoncour +1
There is now ample evidence that Motor Imagery (MI) contributes to improve motor performance. Previous studies provided evidence that its effectiveness remains dependent upon speci…
Fast kernel methods: Sobolev, physics-informed, and additive models
Nathan Doumèche, Francis Bach, Gérard Biau +1
Kernel methods are powerful tools in statistical learning, but their cubic complexity in the sample size n limits their use on large-scale datasets. In this work, we introduce a sc…