SharePoint
Aide
IRSN, Institut de radioprotection et de sûreté nucléaire

Search our site :

ok

Contact us :

ok
En Fr

All our expertise to protect you


Research

Thesis proposals

Machine learning methods for the prediction of multidimensional objects: applications to the reconstruction of spatial data in risk analysis


ReferencesRES21-12

Themes: Mathematics, Physics

Thesis location: Laboratoire de Statistique et des Méthodes Avancées (LSMA)​ - Cadarache

Start: October 2021


Skills required


Master​'s Degree in data Science/Statistics/Applied Mathematics

Age limit: 26 years old unless otherwise stated.


Thesis subject


This thesis is related to the reconstruction of data coming from the safety studies performed at IRSN. In practice, the amount of data, that are experimentally measured or simulated by complex computer codes, is not always substantial enough to precisely capture a phenomenon of interest on its whole variation range. To circumvent this problem, prediction methods are used to approximate the phenomenon where it has not been observed. There exists a large literature on this type of method, several of them exploit the appealing framework of machine learning. However, their adaption to multidimensional objects remains an active field of research under the name object oriented data analysis. This analysis relies on the interpretation of an object as a point in a feature space. Among feature spaces, the Wasserstein space offers an appealing framework for prediction since it allows exploiting optimal transport methods that are efficient for the treatment of complex objects. The objective of the thesis is to establish the connection between classical machine learning approach and optimal transport in order to propose a prediction tool for multidimensional data. A mathematical analysis will be then conducted to quantify the uncertainty associated to the new predictor. Finally, several applications coming from IRSN projects will be performed to validate the new developments and compare them with existing approach of the literature. ​ 

Send Print

Involved IRSN laboratory

Send your resume, cover letter to:


Close

Send to a friend

The information you provide in this page are single use only and will not be saved.
* Required fields

Recipient's email:*  

Sign with your name:* 

Type your email address:*   

Add a message :

Do you want to receive a copy of this email?

Send

Cancel

Close

WP_IMPRIMER_TITLE

WP_IMPRIMER_MESSAGE

Back

Ok