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Shedule -
2022-T3 Geometry & Statistics in Data Sciences
Geometry and Statistics in Data Sciences, Paris
IHP
Amphitheater Darboux
11, Rue Pierre et Marie Curie
75005 Paris
Geometry and Statistics in Data Sciences
Thematic quarter program at Institut Henri Poincaré, Paris
September 5th - December 9th, 2022
Outline
The goal of this Thematic quarter is to highlight the rich interactions between Statistics, Probability theory, Geometry and Topology in the field of Mathematics of AI. It will allow young researchers, Masters students and PhD students to explore cross-disciplinary topics.
Program
- Introductory School at IESC Cargèse (Corsica): 5th - 9th September
- Three Workshops:
- Non-Linear and High Dimensional Inference: 3rd - 7th October
- Geometry, Topology and Statistics in Data Sciences: 10th - 14th October
- Measure-theoretic Approaches and Optimal Transportation in Statistics: 21th - 25th November
- Geomstats Hackathon: 17-21 October
-
Maths-Industry event with AMIES: 8th November
-
General public popularization day: 7th December
- Four lectures and several mini-courses
Long Courses
- Wednesdays 14:00 - 18:00 | Starting September 28th
- Quentin Mérigot (LMO, Orsay)
- Optimal Transport
- Ery Arias-Castro (UC San Diego) and Eddie Aamari (U Paris Cité & Sorbonne U)
- Embedding for Data Analysis : Multidimensional Scaling and Manifold Learning
- Quentin Mérigot (LMO, Orsay)
- Thursdays 9:00 - 13:00 | Starting September 15th
- Eric Klassen (Florida State)
- Geometry of Shape Spaces of Curves and Surfaces
- Wolfgang Polonik (UC Davis)
- Statistical Topological Data Analysis
- Eric Klassen (Florida State)
Mini-Courses
- September, Wednesday 21st AM & PM
- Joseph Yukich (Lehigh University)
- Asymptotic Analysis of Statistics of Random Geometric Structures
- Joseph Yukich (Lehigh University)
- September, Tuesday 27th PM & Wednesday 28th AM
- Nicolas Charon (John Hopkins)
- A Few Applications of Geometric Measure Theory to Shape Analysis
- Nicolas Charon (John Hopkins)
- October, Tuesday 18th PM & Wednesday 19th AM
- Mikhail Belkin (UC San Diego)
- Mathematical Aspects of Deep Learning
- Yusu Wang (UC San Diego)
- TBA
- Mikhail Belkin (UC San Diego)
- November, Tuesday 15th PM & Wednesday 16th AM
- Kathryn Hess (EPFL)
- Topological Approaches to Neuroscience
- Kathryn Hess (EPFL)
- November, Tuesday 29th PM & Wednesday 30th AM
- Stephen Preston
- Riemannian Geometry on Lie Groups
- Stephen Preston
Invited Professors
- Ery Arias-Castro (UC San Diego)
- Martin Bauer (Florida State)
- Mikhail Belkin (UC San Diego)
- Kathryn Hess (EPFL)
- Eric Klassen (Florida State)
- Quentin Mérigot (LMO, Orsay)
- Nina Miolane (UC Santa Barbara)
- Wolfgang Polonik (UC Davis)
- Stephen Preston (Brooklyn College)
- Joseph Yukich (Lehigh University)
- Yusu Wang (UC San Diego)
Scientific Committee
- Charles Bouveyron (Université Côte d’Azur)
- Marco Cuturi (Google Brain, ENSAE)
- Gabor Lugosi (Pompeu Fabra University)
- Pascal Massart (Université Paris-Saclay)
- Mathilde Mougeot (Centre Borelli, ENS Paris-Saclay)
- Xavier Pennec (Inria)
- Sara Van de Geer (ETH Zürich)
Organizing Committee
- 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)
Support