Topology for Learning and Data Analysis
IMT, Toulouse
Sep 30-Oct 4 2019
Mini-courses:
- An Introduction to Topological Data Analysis by F. Chazal (INRIA), B. Michel (Centrale Nantes), P. Massart (U. Orsay)
- A Short Course on Set Estimation by A. Cuevas (U. Madrid)
- Mean-field approximations for inference and learning by R. Eldan (Weizmann Institute)
Research talks:
- Past, Present and Future Results on r-Convex Hull and r-Shapes C. Aaron (U. Clermont-Ferrand)
- Sampling Log-Concave Measures J. Lehec (U. Dauphine)
- Poisson Hulls I. Molchanov (U. Bern)
- Linearization of Wasserstein Space and Stability of Optimal Transport Maps Q. Mérigot (U. Orsay)
- On the Persistent Betti Function and Their Asymptotic Normality W. Polonik (U. California)
- Linking the Theory and Practice of Optimal Transport J. Solomon (MIT)
- Around Unbalanced Optimal Transport F.-X.Vialard (U. Paris Est)
- Two Geometric Problems in Optimal Transport: Discrete and Gaussian Measures Y. Zemel (Cambridge)
Links
Schedules
Commitees
Participants of the workshop
Practical Information (including how to move and lodge in Toulouse)
Registration is free however mandatory (Registration will close 14th of September 2019). Register here.
Students may benefit from funding to cover local expenses (not the travels), please send a letter from your advisor to
- Francesco Costantino <francesco.costantinoATmath.univ-toulouse.fr>
and/or
- Fabrice Gamboa <fabrice.gamboaATmath.univ-toulouse.fr>
Local Organisers: F. Costantino, F. Gamboa
Scientific Committee : M. Arnaudon, J. Bigot, A. Garivier