Publications

Chemical and Process Engineering

Modeling and Study of Hydrodynamic flow within the Preneutralizer Reactor using CFD Approach

S. Elmisaoui, L. Khamar, S. Benjelloun, M. Khamar, J.M. Ghidaglia

Computer Aided Chemical Engineering - 2020

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 - 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

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

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