Theory and Algorithms for the Understanding of Deep learning On Sequential Data
TAUDoS is a 4 years project (2021-2024) funded by the Agence Nationale de la Recherche (French NSF) via the PRCE program.
Its consortium regroups researchers of 5 differents labs:
- The Hubert Curien Laboratory of the Jean Monnet University
- The Laboratoire d’Informatique et Systèmes of the Aix-Marseille University
- The R&D center of the EURA NOVA firm
- The Département d’Informatique et de Recherche Opérationnelle of the Université de Montréal
- The Laboratoire des Sciences du Numérique de Nantes of the Nantes University
The ambition of our project is to provide a better understanding of the mechanisms that allow the amazing recent achievements of Machine Learning, and in particular of Deep Learning. This will be achieved by providing elements that allow a better scientific comprehension of the models, strengthening our experimental results by theoretical guarantees, incorporating components dedicated to interpretability within the models, and allowing trustful quantitative comparison between learned models.
If this sounds interesting to you, please check the dedicated website!