Programme

Chaque jour, l’événement commence à 14h00 (HAEC / UTC+2). Le programme de la conférence est maintenant définitif :

Mon 30/05/2022 Tue 31/05/2022 Wed 01/06/2022
14:00-15:30 Welcome (10 min) Nuwan Herath Arnau Padrol
Gabriel Peyré
(14:10-15:40)
Owen Rouillé
Corentin Lunel
15:30-16:00 Break (20 min) Break (30 min) Break (30 min)
16:00-16:30 Vadim Lebovici Marthe Bonamy
(16:00-17:30)
Arash Vaezi
16:30-17:00 Florent Tallerie Marco Caoduro
17:00-17:10 Break (10 min) Break (10 min)
17:10-17:40 Niloufar Fuladi Break (10 min) Péguy Kem-Meka
17:40-18:10 Daria Pchelina Business meeting Bastien Rivier
18:10-18:40 Minh Quang Le Djamel Eddine Amir
Conclusion (10 min)

Orateurs invités

Cette année des mini-cours et exposés longs seront donnés par les orateurs suivants :

Marthe Bonamy (LaBRI, Université de Bordeaux) – Around the Four Colour Theorem

In this talk we will discuss two crucial tools towards the celebrated Four Colour Theorem: Kempe chains and the discharging method. Both these tools prove to be useful in a variety of contexts, which this talk will not be able to cover in full. Beyond the mere invitation to understand the simple ideas behind this elusive theorem, we hope it will be an entry door to possible connections and applications.

Arnau Padrol (Institut de Mathématiques de Jussieu, Sorbonne Université) – Counting Polytopes

This talk will be an introduction to the enumeration of combinatorial types of convex polytopes. While in dimensions up to 3 we have a very good understanding on the asymptotic growth of the number of polytopes with respect to the number of vertices, in higher dimensions we only have coarse estimates. Upper bounds arise from results of Milnor and Thom from real algebraic geometry, whereas lower bounds are obtained with explicit constructions. I will survey the best bounds up to date.

Gabriel Peyré (DMA, École Normale Supérieure) – Scaling Optimal Transport for High Dimensional Learning

Optimal transport (OT) has recently gained lot of interest in machine learning. It is a natural tool to compare in a geometrically faithful way probability distributions. It finds applications in both supervised learning (using geometric loss functions) and unsupervised learning (to perform generative model fitting). OT is however plagued by the curse of dimensionality, since it might require a number of samples which grows exponentially with the dimension. In this talk, I will explain how to leverage entropic regularization methods to define computationally efficient loss functions, approximating OT with a better sample complexity. More information and references can be found on the website of our book « Computational Optimal Transport » (https://optimaltransport.github.io)

Exposés courts

Djamel Eddine Amir (Université de Lorraine) – Computability of Finite Simplicial Complexes

Marco Caoduro (Laboratoire G-SCOP, Université Grenoble Alpes) – On the Hitting/Packing Ratio of Axis-Parallel Segments

Niloufar Fuladi (Université Gustave Eiffel) – Short Canonical Decomposition for Non-Orientable Surfaces

Nuwan Herath (Inria Nancy-Grand Est) – Fast High-Resolution Drawing of Algebraic Curves

Péguy Kem-Meka Tiotsop Kadzue (University de Ngaoundéré) – Dimensionality Reduction for Persistent Homology

Vadim Lebovici (Université Paris-Saclay, Inria, Laboratoire de mathématiques d’Orsay) – Hybrid Transforms of Constructible Functions

Corentin Lunel (Université Gustave Eiffel) – A Knot Invariant Inspired from Branchwidth and Obstructions

Daria Pchelina (LIPN, Université Sorbonne Paris Nord) – Density of Triangulated Ternary Disc Packings

Minh Quang Le (State University of New York at Buffalo) – Persistent Homology of Convection Cycles in Network Flows

Bastien Rivier (Université Clermont-Auvergne and LIMOS) – Complexity Results on Untangling Planar Rectilinear Red-Blue Matchings

Owen Rouillé (Inria Sophia Antipolis – Méditerranée) – Computing Complete Hyperbolic Structures on Cusped 3-Manifolds

Florent Tallerie (Université Grenoble Alpes) – A Universal Triangulation for Flat Tori

Arash Vaezi (Sharif University of Technology) – Versions of the Art Gallery Problem

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