194 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Laboratoire de Mathématiques d'OrsayFR12 papers
- Institut national de recherche en sciences et technologies du numériqueFR9 papers
- Centre Inria de SaclayFR7 papers
- Laboratoire de Probabilités, Statistique et ModélisationFR6 papers
- Centre National de la Recherche ScientifiqueFR4 papers
- Université Paris-SaclayFR4 papers
- Centre Inria d'Université Côte d'AzurFR3 papers
- École Polytechnique Fédérale de LausanneCH3 papers
- Institut de Mathématiques de ToulouseFR3 papers
- Institut National des Sciences Appliquées de ToulouseFR3 papers
- Université Toulouse III - Paul SabatierFR3 papers
- University of PotsdamDE3 papers
6 papers · 1 filter
Recovering the homology of immersed manifolds
Raphaël Tinarrage
Given a sample of an abstract manifold immersed in some Euclidean space, we describe a way to recover the singular homology of the original manifold. It consists in estimating its…
ATOL: Measure Vectorization for Automatic Topologically-Oriented Learning
Martin Royer, Frédéric Chazal, Clément Levrard +2
Robust topological information commonly comes in the form of a set of persistence diagrams, finite measures that are in nature uneasy to affix to generic machine learning framework…
Spectral Properties of Radial Kernels and Clustering in High Dimensions
David Cohen-Steiner, Alba Chiara de Vitis
In this paper, we study the spectrum and the eigenvectors of radial kernels for mixtures of distributions in . Our approach focuses on high dimensions and relies sole…
PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures
Mathieu Carrière, Frédéric Chazal, Yuichi Ike +3
Persistence diagrams, the most common descriptors of Topological Data Analysis, encode topological properties of data and have already proved pivotal in many different applications…
Convergence analysis of Tikhonov regularization for non-linear statistical inverse learning problems
Abhishake Rastogi, Gilles Blanchard, Peter Mathé
We study a non-linear statistical inverse learning problem, where we observe the noisy image of a quantity through a non-linear operator at some random design points. We consider t…
Understanding the Topology and the Geometry of the Space of Persistence Diagrams via Optimal Partial Transport
Vincent Divol, Théo Lacombe
Despite the obvious similarities between the metrics used in topological data analysis and those of optimal transport, an optimal-transport based formalism to study persistence dia…