29 August 2022 to 2 September 2022
Europe/Paris timezone

Deep learning is becoming a widely used tool in science. This summer school is dedicated to different mathematical aspects of neural networks, with a special focus on applications in computer science and astrophysics.

The summer school is composed of five lectures and three talks. Each lectures (2x1h30) will be complemented by 2 hours of tutorials.

It is primarily intended for the students of the graduate program "Mathematics and interactions : research and interactions" of the University of Strasbourg but is also accessible to any interested PhD student or researcher. No machine learning background is required to attend the summer school. This event is supported by the Interdisciplinary Thematic Institute IRMIA++.

It will take place from 29 August to 2 September in the IRMA conference room at the University of Strasbourg.



  • Introduction to Deep Learning, Léo Bois (Université de Strasbourg)
  • Convolutional Neural Networks for object dectection: fast and accurate results with the YOLO (You Only Look Once) method, David Cornu (Observatoire de Paris)
  • Generative models for images, Bruno Galerne (Université d'Orléans)
  • Deep Learning and dynamical systems: applications in neuroimaging, François Rousseau (IMT Atlantique)
  • Introduction to deep learning on graphs, Samuel Vaiter (CNRS, Université Côté d'Azur)



Salle de conférence
Université de Strasbourg
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  • Clémentine Courtès (IRMA, Université de Strasbourg)
  • Sylvain Faisan (ICUBE, Université de Strasbourg)
  • Jonathan Freundlich (Observatoire Astronomique de Strasbourg)
  • Laurène Hume (ITI IRMIA++, Université de Strasbourg)
  • Laurent Navoret (IRMA, Université de Strasbourg)