Publications

Bioinformatics

The First 3D Model of the Full-Length KIT Cytoplasmic Domain Reveals a New Look for an Old Receptor

Receptor tyrosine kinases (RTKs) are key regulators of normal cellular processes and have a critical role in the development and progression of many diseases. RTK ligand-induced stimulation leads to activation of the cytoplasmic kinase domain that…

François Inizan, Myriam Hanna, Maxim Stolyarchuk, Isaure Chauvot de Beauchêne, Luba Tchertanov

Scientific Reports - 2020

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 - 2020

Machine Learning

Apprenticeship Learning for a Predictive State Representation of Anesthesia

Pierre Humbert, Clément Dubost, Julien Audiffren, Laurent Oudre

IEEE Transactions on Biomedical Engineering - 2020

Fluid mechanics

The turbulent Faraday instability in miscible fluids

Antoine Briard, Louis Gostiaux, Benoît-Joseph Gréa

Journal of Fluid Mechanics - 2020

Analysis of PDEs

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

Analysis of PDEs

An elementary approach to uniform in time propagation of chaos

Based on a coupling approach, we prove uniform in time propagation of chaos for weakly interacting mean-field particle systems with possibly non-convex confinement and interaction potentials. The approach is based on a combination of reflection and…

Alain Durmus, Andreas Eberle, Arnaud Guillin, Raphael Zimmer

Proceedings of the American Mathematical Society - 2020

Methods and statistics

CAD model Segmentation via Deep Learning

Antoine Van Biesbroeck, Feifei Shang, David Bassir

International Journal of Computational Methods - 2020

Statistics

Redundancy in Gaussian random fields

We introduce and study a notion of spatial redundancy in Gaussian random fields. we define similarity functions with some properties and give insight about their statistical properties in the context of image processing. We compute these similarity…

Valentin de Bortoli, Agnès Desolneux, Bruno Galerne, Arthur Leclaire

ESAIM: Probability and Statistics - 2020

History and Overview

Pour un enseignement par la recherche : compte rendu d'un groupe de travail

Didier Lesesvre

Repères IREM - 2020

General Physics

Combining phase-space and time-dependent reduced density matrix approach to describe the dynamics of interacting fermions

The possibility to apply phase-space methods to many-body interacting systems might provide accurate descriptions of correlations with a reduced numerical cost. For instance, the so-called stochastic mean-field phase-space approach, where the…

Thomas Czuba, Denis Lacroix, David Regnier, Ibrahim Ulgen, Bulent Yilmaz

The European physical journal. A, Hadrons and Nuclei - 2020