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EN FR
MODAL - 2019
Overall Objectives
Application Domains
New Results
Bilateral Contracts and Grants with Industry
Bibliography
Overall Objectives
Application Domains
New Results
Bilateral Contracts and Grants with Industry
Bibliography


Section: Partnerships and Cooperations

National Initiatives

Programme of Investments for the Future (PIA)

Bilille is a member of the PIA “Infrastructures en biologie-santé” IFB, French Institute of Bioinformatics (https://www.france-bioinformatique.fr/en). As the co-head of the platform, Guillemette Marot is thus involved in this network.

RHU PreciNASH

Participant : Guillemette Marot.

  • RHU PreciNASH

  • Acronym: PreciNASH

  • Project title: Non-alcoholic steato-hepatitis (NASH) from disease stratification to novel therapeutic approaches

  • Coordinator: F. Pattou

  • Duration: 5 years

  • Partners: FHU Integra and Sanofi

  • Abstract: PreciNASH, project coordinated by Pr. F. Pattou (UMR 859, EGID), aims at better understanding non alcoholic stratohepatitis (NASH) and improving its diagnosis and care. In this RHU, Guillemette Marot supervises a 2 years post-doc, as her team EA 2694 is a member of the FHU Integra. EA 2694 is involved in the WP1 for the development of a clinical-biological model for the prediction of NASH. Other partners of the FHU are UMR 859, UMR 1011 and UMR 8199, these last three teams being part of the labex EGID (European Genomic Institute for Diabetes). Sanofi is the main industrial partner of the RHU PreciNASH. The whole project will last 5 years (2016-2021).

CNRS PEPS Blanc – BayesRealForRNN project

Participants : Pascal Germain, Vera Shalaeva.

  • BayesRealForRNN project: PAC-Bayesian theory for recurrent neural networks: a control theoretic approach

  • Coordinator: Mihaly Petreczky, CNRS, UMR 9189 CRIStAL, Université de Lille

  • Year: 2019

  • Abstract: The project proposes to analyze the mathematical correctness of deep learning algorithms by combining techniques from control theory and PAC-Bayesian statistical theory. More precisely, the project proposes to concentrate on recurrent neural networks (RNNs), develop their structure theory using techniques from contol theory, and then apply this structure theory to derive PAC-Bayesian error bounds for RNNs.

CNRS AMIES PEPS 2 - DiagChange project

Participants : Cristian Preda, Quentin Grimonprez.

  • DiagChange

  • Coordinator: Cristian Preda, Inria MODAL

  • Year: 2019

  • Abstract: The project proposes to study the topic of change detection distribution for multivariate signal in a industrial context.The project is in collaboration with the Diagrams start-up.

AMIES PEPS 1 - CADIS2

Participants : Serge Iovleff, Sophie Dabo-Niang, Cristian Preda.

  • Partners: Société SIRS https://www.sirs-fr.com/sirs/fr/

  • Acronym: CADIS2

  • Project title: Classification Automatique D’Images Sentinel-2

  • Coordinator: Serge Iovleff

  • Year: 2019

  • Duration: 1 year

  • Abstract: In the context of several European projects, SIRS is in charge of exploring the improvements to be made to the "High Resolution Layers" as well as future prototypes such as "CORINE Land Cover +", on a European scale using the Sentinel-2 images, through the project H2020 "ECoLaSS". The CADIS2 project aims to develop, study and implement supervised classification methods to classify trees in predefined forest areas by SIRS.

AMIES PEPS 2 - MadiPa

Participants : Stéphane Girard, Serge Iovleff.

  • Partners: Société Phimeca http://phimeca.com/, Mistis team Inria Grenoble Rhône-Alpes

  • Acronym: MadiPa

  • Project title: Modèles Auto-associatifs pour la Dispersion de Polluants dans l’Atmosphère

  • Coordinator: Stéphane Iovleff

  • Duration: 18 month (start in december 2019)

  • Abstract: Our goal is to develop a method for predicting the dispersion of pollutants in the atmosphere from an initial emission map and meteorological data. A map of the probabilities of exceeding a critical threshold of pollutants will be estimated thanks to the construction of a meta-model: the large dimension of the problem is reduced by the use of auto-associative models, a non-linear extension of the Principal Components Analysis.

ANR

ANR APRIORI

Participants : Benjamin Guedj, Pascal Germain, Hemant Tyagi, Vera Shalaeva.

  • APRIORI 2019–2023, ANR PRC

  • PAC-Bayesian theory and algorithms for deep learning and representation learning.

  • Main coordinator of the project: Emilie Morvant, Université Jean Monnet.

  • Funding: 300k EUR.

  • 2 partners - MODAL (Inria LNE), Hubert Curien Lab. (UMR CNRS 5516).

ANR BEAGLE

Participants : Benjamin Guedj, Pascal Germain.

  • BEAGLE 2019–2023, ANR JCJC

  • PAC-Bayesian theory and algorithms for agnostic learning

  • Main coordinator of the project: Benjamin Guedj

  • Funding: 180k EUR

  • The consortium also includes Pierre Alquier (RIKEN AIP, Japan), Peter Grünwald (CWI, The Netherlands), Rémi Bardenet (UMR CRIStAL 9189).

ANR SMILE

Participants : Christophe Biernacki, Vincent Vandewalle.

  • SMILE Project-2018-2022

  • ANR project (ANR SMILE - Statistical Modeling and Inference for unsupervised Learning at LargE-Scale)

  • Main coordinator of the project: Faicel Chamroukhi, LMNO, Université de Caen

  • 4 partners - MODAL (Inria LNE), LMNO UMR CNRS 6139 (Caen), LMRS UMR CNRS 6085 (Rouen), LIS UMR CNRS 7020 (Toulon).

ANR TheraSCUD2022

Participant : Guillemette Marot.

  • Acronym: TheraSCUD2022

  • Project title: Targeting the IL-20/IL-22 balance to restore pulmonary, intestinal and metabolic homeostasis after cigarette smoking and unhealthy diet

  • Coordinator: P. Gosset

  • Duration: 3 years (2017-2020)

  • Partners: CIIL Institut Pasteur de Lille and UMR 1019 INRA Clermont-Ferrand

  • Abstract: TheraSCUD2022, project coordinated by P. Gosset (Institut Pasteur de Lille), studies inflammatory disorders associated with cigarette smoking and unhealthy diet (SCUD). Guillemette Marot is involved in this ANR project as head of bilille platform, and will supervise 1 year engineer on integration of omic data. The duration of this project is 3 years (2017-2020).

Working groups

  • Sophie Dabo-Niang belongs to the following working groups:

    • STAFAV (STatistiques pour l'Afrique Francophone et Applications au Vivant)

    • ERCIM Working Group on computational and Methodological Statistics, Nonparametric Statistics Team

  • Benjamin Guedj belongs to the following working groups (GdR) of CNRS:

    • ISIS (local referee for Inria Lille - Nord Europe)

    • MaDICS

    • MASCOT-NUM (local referee for Inria Lille - Nord Europe).

  • Guillemette Marot belongs to the StatOmique working group.

Other initiatives

Participants : Serge Iovleff, Cristian Preda, Vincent Vandewalle.

Serge Iovleff is the head of the project CloHe granted in 2016 by the Mastodons CNRS challenge “Big data and data quality”. The project is axed on the design of classification and clustering algorithms for mixed data with missing values with applications to high spatial resolution multispectral satellite image time-series. Website. Cristian Preda and Vincent Vandewalle are also members of the CloHe project.