97 citations
- Centre National de la Recherche ScientifiqueFR41 papers
- Université Paris-SaclayFR36 papers
- Université Paris CitéFR12 papers
- CEA Paris-SaclayFR11 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR11 papers
- École Normale Supérieure Paris-SaclayFR11 papers
- École Normale Supérieure - PSLFR10 papers
- École PolytechniqueFR10 papers
- École Nationale Supérieure d’Informatique pour l’Industrie et l’EntrepriseFR9 papers
- CEA DAM Île-de-FranceFR8 papers
- Centre de Mathématiques Appliquées de l'École polytechniqueFR8 papers
- Michelin (France)FR8 papers
105 papers
Decoupling actions of finite-dimensional Lie groups and of groups of diffeomorphisms in the large deformation framework
Rayane Mouhli, Thomas Pierron
In computational anatomy, the Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework has become a central tool for modeling smooth, invertible transformations between sha…
Blur2seq: Blind Deblurring and Camera Trajectory Estimation from a Single Camera Motion-blurred Image
Guillermo Carbajal, Andrés Almansa, Pablo Musé
Motion blur caused by camera shake, particularly under large or rotational movements, remains a major challenge in image restoration. We propose a deep learning framework that join…
Analysis of kinetic Langevin Monte Carlo under the stochastic exponential Euler discretization from underdamped all the way to overdamped
Kyurae Kim, Samuel Gruffaz, Ji Won Park +1
Simulating the kinetic Langevin dynamics is a popular approach for sampling from distributions, where only their unnormalized densities are available. Various discretizations of th…
Differentiable Expectation-Maximisation and Applications to Gaussian Mixture Model Optimal Transport
Samuel Boïté, Eloi Tanguy, Julie Delon +2
The Expectation-Maximisation (EM) algorithm is a central tool in statistics and machine learning, widely used for latent-variable models such as Gaussian Mixture Models (GMMs). Des…
Deep Generative Methods and Tire Architecture Design
Fouad Oubari, Raphael Meunier, Rodrigue Décatoire +1
As deep generative models proliferate across the AI landscape, industrial practitioners still face critical yet unanswered questions about which deep generative models best suit co…
A Unifying Framework for Global Optimization: From Theory to Formalization
Gaëtan Serré, Argyris Kalogeratos, Nicolas Vayatis
We introduce an abstract measure___theoretic framework that serves as a tool to rigorously study stochastic iterative global optimization algorithms as a unified class. The framewo…