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Publications

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

Affichage des publications 1121 à 1130 sur 1268 au total

Probability

Quantized Variational Inference

We present Quantized Variational Inference, a new algorithm for Evidence Lower Bound minimization. We show how Optimal Voronoi Tesselation produces variance free gradients for Evidence Lower Bound (ELBO) optimization at the cost of introducing…

Amir Dib

Advances in Neural Information Processing Systems (NeurIPS) -

Santé publique et épidémiologie

Endotypes identified by cluster analysis in asthmatics and non-Asthmatics and their clinical characteristics at follow-up: The case-control EGEA study

Background Identifying relevant asthma endotypes may be the first step towards improving asthma management. We aimed identifying respiratory endotypes in adults using a cluster analysis and to compare their clinical characteristics at follow-up…

Rachel Nadif, Mickael Febrissy, Miora Valérie Andrianjafimasy, Nicole Le Moual, Frédéric Gormand, Jocelyne Just, Isabelle Pin, Valérie Siroux, Régis Matran, Orianne Dumas, Mohamed Nadif

BMJ open respiratory research -

Neurons and Cognition

A Multidimensional Data Acquisition as a Preliminary Step to the Secondary Prevention of the Loss of Autonomy for Patients with Traumatic Injury and Stroke: An AMISIA Pilot Study

Background: The aim of our study was to conduct an ad hoc data collection in healthy adults with the intention of extracting individual profiles to study the ability to effectively monitor one's health by extracting relevant indicators. As “each…

Stéphane Mandigout, Anaick Perrochon, Laure Fernandez, Nasser Rezzoug, Benoît Encelle, Ioannis Kanellos, Damien Ricard, Marinette Bouet, Michel Schneider, Stéphane Buffat

Innovation and Research in BioMedical engineering -

Machine Learning

Statistical and Topological Properties of Sliced Probability Divergences

The idea of slicing divergences has been proven to be successful when comparing two probability measures in various machine learning applications including generative modeling, and consists in computing the expected value of a `base divergence'…

Kimia Nadjahi, Alain Durmus, Lénaïc Chizat, Soheil Kolouri, Shahin Shahrampour, Umut Şimşekli

Advances in Neural Processing Systems -

Functional Analysis

A characterization of proximity operators

We characterize proximity operators, that is to say functions that map a vector to a solution of a penalized least squares optimization problem. Proximity operators of convex penalties have been widely studied and fully characterized by Moreau. They…

Rémi Gribonval, Mila Nikolova

Journal of Mathematical Imaging and Vision -

Statistics Theory

Efficient stochastic optimisation by unadjusted Langevin Monte Carlo. Application to maximum marginal likelihood and empirical Bayesian estimation

Stochastic approximation methods play a central role in maximum likelihood estimation problems involving intractable likelihood functions, such as marginal likelihoods arising in problems with missing or incomplete data, and in parametric empirical…

Valentin de Bortoli, Alain Durmus, Marcelo Pereyra, Ana Fernandez Vidal

Statistics and Computing -

Analysis of PDEs

Paralinearization of the Muskat Equation and Application to the Cauchy Problem

We paralinearize the Muskat equation to extract an explicit parabolic evolution equation having a compact form. This result is applied to give a simple proof of the local well-posedness of the Cauchy problem for rough initial data, in homogeneous…

Thomas Alazard, Omar Lazar

Archive for Rational Mechanics and Analysis -