Programmes passés

Programme 2022 :
08/09 : Erhart polynomials and code optimization - Philippe CLAUSS et Thomas DELZANT
22/09 : Drums shape and room acoustics - Antoine DELEFORGE et Yannick PRIVAT
06/10 : Dynamical systems and astrophysics - Giacomo MONARI et Ana Rechtman
22/10 : Causal inference and applications - Marianne CLAUSEL et Etienne BIRMELE
10/11 : Elliptic curves, symbolic proofs and electronic vote - Véronique CORTIER et Pierrick GAUDRY
24/11 : On mesh generation - Frédéric ALAUZET et Pierre KRAEMER
08/12 : Fluid flow simulation and multi-scale spray modelling - Agathe CHOUIPPE et Marc MASSOT

Programme 2021 :
09/09 : Discrete differential geometry and applications - Franck HETROY-WHEELER et Mathieu DESBRUN
23/09 : Symplectic geometry and astrophysics - Rodrigo IBATA et Alexandru OANCEA
07/10 : Turbulence, aeronautics and fluid-particle dynamics - Abderhamane MAROUF et Markus UHLMANN
21/10 : Lung ventilation modelling and high performance computing - Céline GRANDMONT et Hugo LECLERC
04/11 : Discrete geometry for images and point clouds - Etienne BAUDRIER et Quentin MERIGOT
18/11 : Wavelets and astrophysics - Erwan ALLYS et Philippe HELLUY
02/12 : Optimal transport and astrophysics - Nicolas JUILLET et Bruno LEVY

28/08/2023 - 01/09/2023 : Geometry and Data

Optimal transport for data analysis - Laetitia CHAPEL
Shape analysis - Joan GLAUNES
Topological methods for astrophysical data - Katarina KRALJIC
Nonlinear, Geometric Reduced Models for Forward and Inverse Problems - Olga MULA
Geometric transformations on digital images - Phuc NGO
Coverage of astronomical datasets - Sébastien DERRIERE
Multi-scale modeling of natural images with stochastic geometry - Sixin ZHANG

29/08/2022 - 02/09/2022 : Deep Learning and Applications

Introduction to Deep Learning - Léo BOIS
Convolutional Neural Networks for object dectection: fast and accurate results with the YOLO (You Only Look Once) method - David CORNU
Generative models for images - Bruno GALERNE
Deep Learning and dynamical systems: applications in neuroimaging - François ROUSSEAU
Introduction to deep learning on graphs - Samuel VAITER
Rodrigo IBATA
Nicolas PADOY