Thematic program with short courses, seminars and workshops.

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.

This workshop is part of a series of events throughout the fall: IHP Geometry and Statistics in Data Sciences which will include courses that will be posted online soon.

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)
Yohannes Krebs (University of Heidelberg)
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)

Organizers: Eddie Aamari (LPSM, CNRS), Catherine Aaron (LMBP, Université Clermont Auvergne) Frédéric Chazal (LMO, INRIA), Aurélie Fischer (LPSM, Université de Paris) Marc Hoffmann (CEREMADE, Paris Dauphine), Alice Le Brigant (SAMM, Paris 1 Panthéon Sorbonne) Clément Levrard (LPSM, Université de Paris), Bertrand Michel (LMJL, Ecole Centrale Nantes)