Geometry and Statistics in Data Sciences, Paris

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Contributions*

Accueil

Adeline Fermanian- Scaling ResNets in the Large-depth Regime

Agnès Desolneux

Alexander Cloninger - Learning on and near Low-Dimensional Subsets of the Wasserstein Manifold

Arthur Gretton

Atelier GeomStats

Atelier Gudhi

Atelier TTK

Baptiste Labarthe (Metafora) Analyse Topologique des données : applications prometteuses aux données de cytométrie et au diagnostic médical.

Barbara Gris - Defining Data-Driven Deformation Models

Bharath Sriperumbudur

Blanche Buet

Bodhisattva Sen

Botond Szabo- Linear methods for nonlinear inverse problems

Christophe Ley

Claire Brecheteau - Approximating data with a union of ellipsoids and clustering.

Claire Lacour - On the use of overfitting for estimator selection

Claudia Strauch- On high-dimensional Lévy-driven Ornstein–Uhlenbeck processes

Clément Berenfeld- Understanding the geometry of high-dimensional data through the reach

Cocktail

Cocktail

Cocktail (Tour Zamansky, Jussieu)

Damien Garreau - What does LIME really see in images?

Denis Belometsny- Dimensionality reduction in reinforcement learning by randomisation

Dominique Attali- Reconstructing manifolds by weighted ${\ell }_1$-norm minimization

Elsa Cazelles

Eric Klassen (The Square Root Normal Field and Unbalanced Optimal Transport)

Eric Klassen - Geometry of Shape Spaces of Curves and Surfaces (1/9)

Eric Klassen - Geometry of Shape Spaces of Curves and Surfaces (2/9)

Eric Klassen - Geometry of Shape Spaces of Curves and Surfaces (3/9).

Eric Klassen - Geometry of Shape Spaces of Curves and Surfaces (4/9).

Eric Klassen - Geometry of Shape Spaces of Curves and Surfaces (5/9).

Eric Klassen - Geometry of Shape Spaces of Curves and Surfaces (6/9).

Eric Klassen - Geometry of Shape Spaces of Curves and Surfaces (7/9)

Eric Klassen - Geometry of Shape Spaces of Curves and Surfaces (8/9).

Eric Klassen - Geometry of Shape Spaces of Curves and Surfaces (9/9).

Ery Arias-Castro & Eddie Aamari - Embedding for Data Analysis (1/8)

Ery Arias-Castro & Eddie Aamari - Embedding for Data Analysis (2/8)

Ery Arias-Castro & Eddie Aamari - Embedding for Data Analysis (3/8)

Ery Arias-Castro & Eddie Aamari - Embedding for Data Analysis (4/8)

Ery Arias-Castro & Eddie Aamari - Embedding for Data Analysis (5/8)

Ery Arias-Castro & Eddie Aamari - Embedding for Data Analysis (6/8)

Ery Arias-Castro & Eddie Aamari - Embedding for Data Analysis (7/8)

Ery Arias-Castro & Eddie Aamari - Embedding for Data Analysis (8/8)

Franck Picard - A probabilistic Graph Coupling View of Dimension Reduction

François-Xavier Vialard

Frédéric Barbaresco -Symplectic Foliation Model of Information Geometry for Statistics and Learning on Lie Groups

Gabriel Peyré

Geometric Statistic

Geometric Statistic

Geometric Statistic

Geometric Statistic

Geometric Statistic

Gilles Blanchard - Stein effect for estimating many vector means: a "blessing of dimensionality" phenomenon

Giovanni Peccati

Heather Harington- shape of data in biology.

Herbert Edelsbrunner - Chromatic Delaunay mosaics for chromatic point data.

High Dimensional Statistics

High Dimensional Statistics

High Dimensional Statistics

High Dimensional Statistics

High Dimensional Statistics

Introduction

Introduction de la journée (AMIES & Semestre Gesda).

Irène Kaltenmark - Curves and surfaces. Partial matching in the space of varifolds.

Jean Feydy

Joannes Krebs -On the law of the iterated logarithm and Bahadur representation in stochastic geometry

Johan Segers

Johannes Schmidt-Hieber - A statistical analysis of an image classification problem

John Harlim- Leveraging the RBF operator estimation for manifold learning.

Joseph Yukich - Asymptotic Analysis of Random Geometric Structures (2/2)

Joseph Yukich - Asymptotic Analysis of Statistics of Random Geometric Structures (1/2)

Judith Rousseau- Bayesian nonparametric estimation of a density living near an unknown manifold

Jérôme Dedecker

Katharine Turner - The Extended Persistent Homology Transform for Manifolds with Boundary

Kathryn Hess - Topological Approaches to Neuroscience (1/2).

Kathryn Hess - Topological Approaches to Neuroscience (2/2)

Kathryn Hess -Morse-theoretic signal compression and reconstruction

Klervi Le Gall (UN) Analyse en Composantes Principales sur l’espace des fonctions à valeurs sur la variété des rotations 3-dimensionnelles: application à l’évaluation du déficit ambulatoire chez les patients atteints de SEP.

Laurent Younes -Stochastic Gradient Descent for Large-Scale LDDMM

Marina Meila - Manifold Learning, Explanations and Eigenflows

Martin Bauer -Elastic Shape Analysis of Surface

Mikhail Belkin - Mathematical Aspects of Deep Learning (1/2)

Mikhail Belkin - Mathematical Aspects of Deep Learning (2/2)

Mikhail Belkin- Neural networks, wide and deep, singular kernels and Bayes optimality

Nicolas Charon - A Few Applications of Geometric Measure Theory to Shape Analysis (1/2)

Nicolas Charon - A Few Applications of Geometric Measure Theory to Shape Analysis (2/2)

Nicolas Charon - Registration of shape graphs with partial matching constraints

Nicolas Courty

Nicolas Verzelen - Optimal Permutation Estimation in Crowd-Sourcing problems

Nina Miolane -Geomstats: a Python package for Geometric Machine Learning

Olga Mula

Omer Bobrowski -Universality in Random persistence Diagrams

Peter Bartlett - The Dynamics of Sharpness-Aware Minimization.

posters

Présentation commune des librairies et plateformes GeomStats, Gudhi et TTK.

Quentin Berthet

Quentin Mérigot - Optimal Transport (1/8)

Quentin Mérigot - Optimal Transport (2/8)

Quentin Mérigot - Optimal Transport (3/8)

Quentin Mérigot - Optimal Transport (4/8)

Quentin Mérigot - Optimal Transport (5/8)

Quentin Mérigot - Optimal Transport (6/8)

Quentin Mérigot - Optimal Transport (7/8)

Quentin Mérigot - Optimal Transport (8/8)

Quentin Paris

Registration

Rémi Perrichon (ENAC) Statistique et géométrie au service de l’analyse de trajectoires d’avions.

Sophie Langer- Overcoming the curse of dimensionality with deep neural networks

Stefan Sommer -Diffusions means in geometric statistics

Stephen Preston - Isometric immersions and the waving of flags

Stephen Preston - Riemannian Geometry on Lie Groups (1/2)

Stephen Preston - Riemannian Geometry on Lie Groups (2/2)

Steve Oudot (Optimization in topological data analysis)

Table ronde avec Frédéric Barbaresco (Thales), Nicolas Bousquet (EDF) et Stéphanie Allassonnière (Univ. Paris Cité).

Thibaut Le Gouic

Théo Lacombe

Topological Data Analysis

Topological Data Analysis

Topological Data Analysis

Topological Data Analysis

Topological Data Analysis

Vasiliki Velona - Learning a partial correlation graph using only a few covariance queries.

Victor Patrangenaru -Geometry, Topology and Statistics on Object Spaces

Wolfgang Polonik - Statistical Topological Data Analysis (1/9)

Wolfgang Polonik - Statistical Topological Data Analysis (2/9)

Wolfgang Polonik - Statistical Topological Data Analysis (3/9)

Wolfgang Polonik - Statistical Topological Data Analysis (4/9)

Wolfgang Polonik - Statistical Topological Data Analysis (5/9)

Wolfgang Polonik - Statistical Topological Data Analysis (6/9).

Wolfgang Polonik - Statistical Topological Data Analysis (7/9).

Wolfgang Polonik - Statistical Topological Data Analysis (8/9).

Wolfgang Polonik - Statistical Topological Data Analysis (9/9).

Wolfgang Polonik- Topologically penalized regression on manifolds

Yusu Wang - Some Theoretical Aspects of Graph Neural Networks (and Higher Order Variants) (1/2)

Yusu Wang - Some Theoretical Aspects of Graph Neural Networks (and Higher Order Variants) (2/2)

Yusu Wang -Weisfeiler-Lehman Meets Gromov-Wasserstein

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