Geometry, Topology and Statistics in Data Sciences
10-14 October - IHP, Paris
On one hand, modern data science makes use of Topological Data Analysis in a preliminary step to obtain structural information before processing supervised or unsupervised methods. On the other hand, when a priori knowledge of a Riemannian manifold containing the data is available, shape analysis proposes to adapt mathematical statistics tools to infer geometric and statistical properties.
Invited Speakers
- Dominique Attali (GIPSA-lab)
- Martin Bauer (Florida State University)
- Omer Bobrowski (Technion Israel Institute of Technology)
- Claire Brécheteau (University Rennes 2)
- Nicolas Charon (Johns Hopkins University)
- Herbert Edelsbrunner (Institute of Science and Technology Austria)
- Barbara Gris (Sorbonne University)
- Heather Harrington (Oxford University)
- Kathryn Hess (EPFL)
- Eric Klassen (Florida State University)
- Johannes Krebs (KU Eichstaett)
- Nina Miolane (UC Santa Barbara)
- Stephen Preston (City University of New York)
- Stefan Horst Sommer (University of Copenhagen)
- Katharine Turner (Australian National University)
- Yusu Wang (UC San Diego)
- Laurent Younes (Johns Hopkins University)
Application
Application for this event is currently open.