Vincent Divol

Présentation

Publications

Article dans une revue (6)

Measure estimation on a manifold explored by a diffusion process Vincent Divol,Hélène Guérin,Dinh-Toan Nguyen,Viet Chi Tran Probability Theory and Related Fields, 2025, ⟨10.1007/s00440-025-01437-x⟩ Article dans une revue hal-05311560v1
Measure estimation on manifolds: an optimal transport approach Vincent Divol Probability Theory and Related Fields, 2022 Article dans une revue hal-03141977v2
Minimax adaptive estimation in manifold inference Vincent Divol Electronic Journal of Statistics , 2021, ⟨10.1214/21-EJS1934⟩ Article dans une revue hal-02440881v3
Understanding the Topology and the Geometry of the Space of Persistence Diagrams via Optimal Partial Transport Vincent Divol,Théo Lacombe Journal of Applied and Computational Topology, 2020, ⟨10.1007/s41468-020-00061-z⟩ Article dans une revue hal-01970466v4
The density of expected persistence diagrams and its kernel based estimation Frédéric Chazal,Vincent Divol Journal of Computational Geometry, 2019, 10 (2), ⟨10.20382/jocg.v10i2a7⟩ Article dans une revue hal-04308723v1
On the choice of weight functions for linear representations of persistence diagrams Vincent Divol,Wolfgang Polonik Journal of Applied and Computational Topology, 2019, 3 (3), pp.249-283. ⟨10.1007/s41468-019-00032-z⟩ Article dans une revue hal-01833660v3

Communication dans un congrès (4)

Wasserstein convergence of Čech persistence diagrams for samplings of submanifolds Charles Arnal,David Cohen-Steiner,Vincent Divol NeurIPS 2024 - The Thirty-Eighth Annual Conference on Neural Information Processing Systems, Dec 2024, Vancouver (Canada), Canada Communication dans un congrès hal-04617508v1
Minimax estimation of discontinuous optimal transport maps: The semi-discrete case Aram-Alexandre Pooladian,Vincent Divol,Jonathan Niles-Weed International Conference on Machine Learning, Jul 2023, Honolulu, United States Communication dans un congrès hal-04352861v1
Estimation and Quantization of Expected Persistence Diagrams Vincent Divol,Théo Lacombe ICML 2021 - 38th International Conference on Machine Learning, Jul 2021, Virtual Conference, United States. ⟨10.48550/arXiv.2105.04852⟩ Communication dans un congrès hal-03222657v1
The density of expected persistence diagrams and its kernel based estimation Frédéric Chazal,Vincent Divol SoCG 2018 - Symposium of Computational Geometry, Jun 2018, Budapest, Hungary Communication dans un congrès hal-01716181v3

Pré-publication, Document de travail (4)

Minimax spectral estimation of weighted Laplace operators Yann Chaubet,Vincent Divol 2025 Pré-publication, Document de travail hal-05429210v1
Critical points of the distance function to a generic submanifold Charles Arnal,David Cohen-Steiner,Vincent Divol 2024 Pré-publication, Document de travail hal-04471485v1
Demographic parity in regression and classification within the unawareness framework Vincent Divol,Solenne Gaucher 2024 Pré-publication, Document de travail hal-04684789v1
A short proof on the rate of convergence of the empirical measure for the Wasserstein distance Vincent Divol 2021 Pré-publication, Document de travail hal-03117283v1