A summer school on deep learning and applications will take place in Strasbourg from August 29th to September 2nd. The summer school is dedicated to different mathematical aspects of neural networks and deep learning with a special focus on applications in computer science and astrophysics.
It consists of 5 lectures, each complemented by tutorials and 3 talks. Although the school is primarily intended for the students of the graduate program "Mathematics and interactions : research and interactions" of the University of Strasbourg, it remains accessible to any interested PhD students and researchers. No machine learning background is required to attend the summer school.
List of the lectures:
- Introduction to Deep Learning, Léo Bois (Université de Strasbourg)
- Convolutional Neural Networks for object detection: 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)
Application deadline: 24 June 2022.
For reasons of room capacity during the tutorial sessions, registration (free but mandatory) is subject to validation by the organizers.
Registration and details on the dedicated website
The organizers
Clémentine Courtès, Sylvain Faisan, Jonathan Freundlich, Laurène Hume, Laurent Navoret
summerschool2022[at]math.unistra.fr