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RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds

 Felix Hensel , Marc Glisse , Frédéric Chazal , Thibault de Surrel , Mathieu Carriere , et al.
Proceedings of Machine Learning Research, 2022, Proceedings of Topological, Algebraic, and Geometric Learning Workshops 2022, 196, pp.96-106
Article dans une revue hal-03867083v1
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Optimizing persistent homology based functions

 Mathieu Carriere , Frédéric Chazal , Marc Glisse , Yuichi Ike , Hariprasad Kannan
ICML 2021 - 38th International Conference on Machine Learning, Jul 2021, Virtual conference, United States. pp.1294-1303
Communication dans un congrès hal-02969305v2
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Statistical analysis and parameter selection for Mapper

 Mathieu Carriere , Bertrand Michel , Steve Y. Oudot
Journal of Machine Learning Research, 2018
Article dans une revue hal-01633106v2
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Persistent homology based characterization of the breast cancer immune microenvironment: a feasibility study

 Andrew Aukerman , Mathieu Carriere , Chao Chen , Kevin Gardner , Raúl Rabadán , et al.
Journal of Computational Geometry, 2022, Special Issue of Selected Papers from SoCG 2020, 12 (2), pp.183-206. ⟨10.20382/jocg.v12i2a9⟩
Article dans une revue hal-03912324v1
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Topological Data Analysis and its usefulness for precision medicine studies

 Raquel Iniesta , Ewan Carr , Mathieu Carriere , Naya Yerolemou , Bertrand Michel , et al.
Sort: Statistics and Operations Research Transactions, 2022, 46 (1), ⟨10.2436/20.8080.02.120⟩
Article dans une revue hal-03912322v1
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Local Equivalence and Intrinsic Metrics Between Reeb Graphs

 Mathieu Carriere , Steve Y. Oudot
International Symposium on Computational Geometry, Jul 2017, Brisbane, Australia
Communication dans un congrès hal-01633109v1
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A Gradient Sampling Algorithm for Stratified Maps with Applications to Topological Data Analysis

 Jacob Leygonie , Mathieu Carrière , Théo Lacombe , Steve Oudot
Mathematical Programming, 2023, 202, pp.199-239. ⟨10.1007/s10107-023-01931-x⟩
Article dans une revue hal-03330940v2
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Stable topological signatures for points on 3D shapes

 Mathieu Carriere , Steve Oudot , Maks Ovsjanikov
Symposium on Geometry Processing, Jul 2015, Graz, Austria
Communication dans un congrès hal-01203716v2

Identifying homogeneous subgroups of patients and important features: a topological machine learning approach

 Ewan Carr , Mathieu Carriere , Bertrand Michel , Frédéric Chazal , Raquel Iniesta
BMC Bioinformatics, 2021, 22, pp.449. ⟨10.1186/s12859-021-04360-9⟩
Article dans une revue hal-03368489v1
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Fast, Stable and Efficient Approximation of Multi-parameter Persistence Modules with MMA

 David Loiseaux , Mathieu Carriere , Andrew Blumberg
2023
Pré-publication, Document de travail hal-03689199v2
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Multiparameter Persistence Images for Topological Machine Learning

 Mathieu Carriere , Andrew J Blumberg
NeurIPS 2020 - 33rd Conference on Neural Information Processing Systems, Dec 2020, Vancouver / Virtuel, Canada
Communication dans un congrès hal-03112442v1
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Structure and Stability of the 1-Dimensional Mapper

 Mathieu Carriere , Steve Y. Oudot
Foundations of Computational Mathematics, 2017, pp.1-64. ⟨10.1007/s10208-017-9370-z⟩
Article dans une revue hal-01633101v2

Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures

 David Loiseaux , Luis Scoccola , Mathieu Carrière , Magnus Bakke Botnan , Steve Oudot
NeurIPS 2023 - 36th Conference on Neural Information Processing Systems, Dec 2023, New Orleans (LA), United States
Communication dans un congrès hal-04133009v1

Statistical analysis of Mapper for stochastic and multivariate filters

 Mathieu Carriere , Bertrand Michel
Journal of Applied and Computational Topology, 2022, 6 (3), pp.331-369. ⟨10.1007/s41468-022-00090-w⟩
Article dans une revue hal-03912325v1

PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures

 Mathieu Carriere , Frédéric Chazal , Yuichi Ike , Théo Lacombe , Martin Royer , et al.
International Conference on Artificial Intelligence and Statistics, Aug 2020, Virtual, Italy
Communication dans un congrès hal-03112050v1

RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds

 Thibault de Surrel , Felix Hensel , Mathieu Carriere , Théo Lacombe , Yuichi Ike , et al.
ICLR 2022 Workshop on Geometrical and Topological Representation Learning, Apr 2022, Virtual conference, United States
Communication dans un congrès hal-03560450v1
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Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs

 Théo Lacombe , Yuichi Ike , Mathieu Carriere , Frédéric Chazal , Marc Glisse , et al.
IJCAI 2021 - 30th International Joint Conference on Artificial Intelligence, Aug 2021, Montréal, Canada. pp.2666-2672, ⟨10.24963/ijcai.2021/367⟩
Communication dans un congrès hal-03213188v1
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Topology identifies emerging adaptive mutations in SARS-CoV-2

 Michael Bleher , Lukas Hahn , Juanángel Patiño-Galindo , Mathieu Carriere , Ulrich Bauer , et al.
2021
Pré-publication, Document de travail hal-03368477v1

Structure and Stability of the 1-Dimensional Mapper

 Mathieu Carriere , Steve Oudot
International Symposium on Computational Geometry, Jun 2016, Boston, United States
Communication dans un congrès hal-01247511v1
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On Metric and Statistical Properties of Topological Descriptors for geometric Data

 Mathieu Carriere
Computational Geometry [cs.CG]. Université Paris-Saclay, 2017. English. ⟨NNT : 2017SACLS433⟩
Thèse tel-01659347v2
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Local Signatures using Persistence Diagrams

 Mathieu Carriere , Steve Oudot , Maks Ovsjanikov
2015
Pré-publication, Document de travail hal-01159297v2

MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks

 Felix Hensel , Charles Arnal , Mathieu Carrière , Théo Lacombe , Hiroaki Kurihara , et al.
2023
Pré-publication, Document de travail hal-04103272v1
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A General Neural Network Architecture for Persistence Diagrams and Graph Classification

 Mathieu Carriere , Frédéric Chazal , Yuichi Ike , Théo Lacombe , Martin Royer , et al.
2019
Pré-publication, Document de travail hal-02105788v1
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Sliced Wasserstein Kernel for Persistence Diagrams

 Mathieu Carriere , Marco Cuturi , Steve Y. Oudot
International Conference on Machine Learning, Aug 2017, Sydney, Australia
Communication dans un congrès hal-01633105v1

A Framework for Fast and Stable Representations of Multiparameter Persistent Homology Decompositions

 David Loiseaux , Mathieu Carrière , Andrew J. Blumberg
NeurIPS 2023 - 36th Conference on Neural Information Processing Systems, Dec 2023, New Orleans (LA), United States
Communication dans un congrès hal-04135811v1
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Differentiable mapper for topological optimization of data representation

 Ziyad Oulhaj , Mathieu Carrière , Bertrand Michel
2024
Pré-publication, Document de travail hal-04457645v1
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