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Publications

Cette page présente les publications du Centre Borelli déposées sur le serveur HAL.

Affichage des publications 981 à 990 sur 1102 au total

Optimization and Control

Convergence Analysis of Riemannian Stochastic Approximation Schemes

This paper analyzes the convergence for a large class of Riemannian stochastic approximation (SA) schemes, which aim at tackling stochastic optimization problems. In particular, the recursions we study use either the exponential map of the…

Alain Durmus, Pablo Jiménez, Eric Moulines, Salem Said, Hoi-To Wai

Materials Science

The Abinit project: impact, environment and recent developments

Abinit is a material- and nanostructure-oriented package that implements density-functional theory (DFT) and many-body perturbation theory (MBPT) to find, from first principles, numerous properties including total energy, electronic structure,…

Xavier Gonze, Bernard Amadon, Gabriel Antonius, Frédéric Arnardi, Lucas Baguet, Jean-Michel Beuken, Jordan Bieder, François Bottin, Johann Bouchet, Eric Bousquet, Nils Brouwer, Fabien Bruneval, Guillaume Brunin, Théo Cavignac, Jean-Baptiste Charraud, Wei Chen, Michel Côté, Stefaan Cottenier, Jules Denier, Grégory Geneste, Philippe Ghosez, Matteo Giantomassi, Yannick Gillet, Olivier Gingras, Donald R Hamann, Geoffroy Hautier, Xu He, Nicole Helbig, Natalie Holzwarth, Yongchao Jia, François Jollet, William Lafargue-Dit-Hauret, Kurt Lejaeghere, Miguel Al Marques, Alexandre Martin, Cyril Martins, Henrique Pc Miranda, Francesco Naccarato, Kristin A Persson, Guido Petretto, Valentin Planes, Yann Pouillon, Sergei Prokhorenko, Fabio Ricci, Gian-Marco Rignanese, Aldo H Romero, Michael Marcus Schmitt, Marc Torrent, Michiel J Van Setten, Benoit Van Troeye, Matthieu J Verstraete, Gilles Zérah, Josef W Zwanziger

Computer Physics Communications -

Computer Science

Taming Nuclear Complexity with a Committee of Multilayer Neural Networks

We demonstrate that a committee of deep neural networks is capable of predicting the ground-state and excited energies of more than 1800 atomic nuclei with an accuracy akin to the one achieved by state-of-the-art nuclear energy density functionals …

Raphaël-David Lasseri, David Regnier, Jean-Paul Ebran, Antonin Penon

Physical Review Letters -

Computer Vision and Pattern Recognition

Robust estimation of local affine maps and its applications to image matching

The classic approach to image matching consists in the detection, description and matching of keypoints. This defines a zero-order approximation of the mapping between two images, determined by corresponding point coordinates. But the patches around…

Mariano Rodríguez, Gabriele Facciolo, Rafael Grompone von Gioi, Pablo Musé, Julie Delon

Winter Conference on Applications of Computer Vision (WACV ’20) -

Medical Imaging

Fidelity metrics between curves and surfaces: currents, varifolds, and normal cycles

This chapter provides an overview of some mathematical and computational models that have been proposed over the past few years for defining data attachment terms on shape spaces of curves or surfaces. In all these models shapes are seen as elements…

Nicolas Charon, Benjamin Charlier, Joan Glaunès, Pietro Gori, Pierre Roussillon

Riemannian Geometric Statistics in Medical Image Analysis -

Machine Learning

An adaptive stochastic optimization algorithm for resource allocation

We consider the classical problem of sequential resource allocation where a decision maker must repeatedly divide a budget between several resources, each with diminishing returns. This can be recast as a specific stochastic optimization problem…

Xavier Fontaine, Shie Mannor, Vianney Perchet

The 31st International Conference on Algorithmic Learning Theory -