The thematic quarter at Institut Henri Poincaré (IHP, Paris) on Geometry and Statistics in Data Sciences, has now started! Its program extends throughout Fall, until December. For the most part, the events will be broadcast online.
Mini-courses and long courses
The invited professors, resident at IHP, will give both mini-courses (~2x1h30) and long courses (~10 lectures throughout Fall), at a research/Masters level.
- Optimal Transport (Quentin Mérigot)
- Embedding for Data Analysis : Multidimensional Scaling and Manifold Learning (Ery Arias-Castro & Eddie Aamari)
- Geometry of Shape Spaces of Curves and Surfaces (Eric Klassen)
- Statistical Topological Data Analysis (Wolfgang Polonik)
- Asymptotic Analysis of Statistics of Random Geometric Structures (Joseph Yukich)
- A Few Applications of Geometric Measure Theory to Shape Analysis (Nicolas Charon)
- Mathematical Aspects of Deep Learning (Mikhail Belkin)
- Some Theoretical Aspects of Graph Neural Networks and Higher Order Variants (Yusu Wang)
- Topological Approaches to Neuroscience (Kathryn Hess)
- Riemannian Geometry on Lie Groups (Stephen Preston)
The complete program is available here.
Three one-week conferences
- Non linear and high-dimensional inference (3-7 October)
- Geometry, topology and statistics in data science (10-14 October)
- Measure-theoretic approaches and optimal transport (21-25 November)
Registration, to each conference separately, is free but compulsory.
Please check “Remote participation” when registering if you want to attend online.
- Open contributions to the library Geomstats (17-21 October)
- Maths-industry day with AMIES (8 November)
- Popularization day (TBA)
Although these events will be broadcast online, we hope to see you many at IHP during the upcoming weeks.
The organizing committee,Eddie Aamari, Catherine Aaron, Frédéric Chazal, Aurélie Fischer, Marc Hoffmann, Alice Le Brigant, Clément Levrard et Bertrand Michel