Publications

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 - 2020

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 - 2020

Mathematics

Sub-Riemannian Methods in Shape Analysis

Laurent Younes, Barbara Gris, Alain Trouvé

Handbook of Variational Methods for Nonlinear Geometric Data - 2020

Mathematics

Microtubules (MT) a key target in oncology: mathematical modeling of anti-MT agents on cell migration

Microtubules (MTs) are protein filaments found in all eukaryotic cells which are crucial for many cellular processes including cell movement, cell differentiation, and cell division, making them a key target for anti-cancer treatment. In particular,…

Emilie Denicolai, Stéphane Honoré, Florence Hubert, Rémi Tesson

Mathematical Modelling of Natural Phenomena - 2020

Mathematics

Lyapunov Functions, Identities and the Cauchy Problem for the Hele–Shaw Equation

This article is devoted to the study of the Hele-Shaw equation. We introduce an approach inspired by the water-wave theory. Starting from a reduction to the boundary, introducing the Dirichlet to Neumann operator and exploiting various cancellations…

Thomas Alazard, Nicolas Meunier, Didier Smets

Communications in Mathematical Physics - 2020

Embedded Systems

Budget learning based on equivalent trees and genetic algorithm : application to fall detection algorithm embedding

Budget learning is a research field of growing interest that aims at including real world resource constraints into the design of machine learning models, mainly to reduce real environment prediction time. One common way of doing it is by modifying…

Mounir Atiq, Sergio Peignier, Mathilde Mougeot

Quantitative Methods

Le premier modèle 3D du domaine cytoplasmique complet du récepteur d'activité tyrosine kinase KIT dévoile une nouvelle vision sur cette ancienne cible

Luba Tchertanov

Scooped by Life Sciences UPSaclay From www.nature.com/articles/s41598-020-62460-7. http://sco.lt/5Pyvei - 2020

Santé publique et épidémiologie

SEAIR Framework Accounting for a Personalized Risk Prediction Score: Application to the Covid-19 Epidemic

The aim of the present work is to provide an SEAIR framework which takes a personalized risk prediction score as an additional input. Each individual is categorized depending on his actual status with respect to the disease – moderate or severe…

Oliver Boulant, Mathilde Fekom, Camille Pouchol, Theodoros Evgeniou, Anton Ovchinnikov, Raphaël Porcher, Nicolas Vayatis

Image Processing On Line - 2020

Tissues and Organs

Développement et validation d'un outil de prédiction du risque de chute chez la personne âgée institutionnalisée

The fall of the elderly is a public health issue because of the medical, social and economic consequences it has. In addition to the serious consequences caused by falls, these accidents can lead to behaviours that reduce daily living activities and…

Flavien Quijoux

Life Sciences

Ethical and social implications of approaching death prediction in humans - when the biology of ageing meets existential issues

Abstract Background The discovery of biomarkers of ageing has led to the development of predictors of impending natural death and has paved the way for personalised estimation of the risk of death in the general population. This study intends to…

Marie Gaille, Marco Araneda, Clément Dubost, Clémence Guillermain, Sarah Kaakai, Elise Ricadat, Nicolas Todd, Michael Rera

BMC Medical Ethics - 2020