Uncertainty Quantification for Physical and Artificial Intelligence systems

Project funding and duration:

The project is funded by the ANITI AI cluster from 2024 to 2028 (€350 000), thanks to the "Starting Chair" instrument (SC).

Project members:

• François Bachoc, Institut de Mathématiques de Toulouse (principal investigator)
  
• Mélisande Albert, Institut de Mathématiques de Toulouse
  
• Nathalie Bartoli, ONERA Toulouse
  
• Sylvain Dubreuil, ONERA Toulouse
  
• Jérôme Morio, ONERA Toulouse
  
• Paul Novello, IRT Saint Exupery
• Robert Koprinkov, PhD student, Institut de Mathématiques de Toulouse and ONERA Toulouse

Summary of the project:

This project aims for new methods in uncertainty quantification applicable to both physical and AI systems. The three main axes are the following.

• Sensitivity analysis
• Bayesian active learning
• Real-world applications

How to acknowledge funding from the project:

• This work was supported by the Chair UQPhysAI of the Toulouse ANITI AI Cluster.