Mathieu Carrière

ORCID

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 39

Top Venues

University of Paris-Sud, Orsay, France (PHD)

Education History

University of Paris-Sud, Orsay, France

PHD

Publications

Mathieu Carrière, Marc Theveneau, Théo Lacombe
Diffeomorphic interpolation for efficient persistence-based topological optimization. CoRR (2024)
Charles Arnal, Felix Hensel, Mathieu Carrière, Théo Lacombe, Hiroaki Kurihara, Yuichi Ike, Frédéric Chazal
MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Neural Networks. Trans. Mach. Learn. Res. 2024 (2024)
Luis Scoccola, Siddharth Setlur, David Loiseaux, Mathieu Carrière, Steve Oudot
Differentiability and Optimization of Multiparameter Persistent Homology. CoRR (2024)
Ziyad Oulhaj, Mathieu Carrière, Bertrand Michel
Differentiable Mapper For Topological Optimization Of Data Representation. CoRR (2024)
Jacob Leygonie, Mathieu Carrière, Théo Lacombe, Steve Oudot
A gradient sampling algorithm for stratified maps with applications to topological data analysis. Math. Program. 202 (1) (2023)
Felix Hensel, Charles Arnal, Mathieu Carrière, Théo Lacombe, Hiroaki Kurihara, Yuichi Ike, Frédéric Chazal
MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks. CoRR (2023)
David Loiseaux, Luis Scoccola, Mathieu Carrière, Magnus Bakke Botnan, Steve Oudot
Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures. CoRR (2023)
David Loiseaux, Mathieu Carrière, Andrew J. Blumberg
A Framework for Fast and Stable Representations of Multiparameter Persistent Homology Decompositions. CoRR (2023)
David Loiseaux, Luis Scoccola, Mathieu Carrière, Magnus Bakke Botnan, Steve Oudot
Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures. NeurIPS (2023)
David Loiseaux, Mathieu Carrière, Andrew J. Blumberg
A Framework for Fast and Stable Representations of Multiparameter Persistent Homology Decompositions. NeurIPS (2023)
David Loiseaux, Mathieu Carrière, Andrew J. Blumberg
Efficient Approximation of Multiparameter Persistence Modules. CoRR (2022)
Mathieu Carrière, Bertrand Michel
Statistical analysis of Mapper for stochastic and multivariate filters. J. Appl. Comput. Topol. 6 (3) (2022)
Thibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frédéric Chazal
RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds. TAG-ML (2022)
Thibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frédéric Chazal
RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds. CoRR (2022)
Ewan Carr, Mathieu Carrière, Bertrand Michel, Frédéric Chazal, Raquel Iniesta
Identifying homogeneous subgroups of patients and important features: a topological machine learning approach. BMC Bioinform. 22 (1) (2021)
Jacob Leygonie, Mathieu Carrière, Théo Lacombe, Steve Oudot
A Gradient Sampling Algorithm for Stratified Maps with Applications to Topological Data Analysis. CoRR (2021)
Théo Lacombe, Yuichi Ike, Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuhei Umeda
Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs. CoRR (2021)
Théo Lacombe, Yuichi Ike, Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuhei Umeda
Topological Uncertainty: Monitoring Trained Neural Networks through Persistence of Activation Graphs. IJCAI (2021)
Michael Bleher, Lukas Hahn, Juan Ángel Patino-Galindo, Mathieu Carrière, Ulrich Bauer, Raul Rabadan, Andreas Ott
Topology identifies emerging adaptive mutations in SARS-CoV-2. CoRR (2021)
Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan, Yuhei Umeda
Optimizing persistent homology based functions. ICML (2021)
Andrew J. Blumberg, Mathieu Carrière, Michael A. Mandell, Raul Rabadan, Soledad Villar
MREC: a fast and versatile framework for aligning and matching point clouds with applications to single cell molecular data. CoRR (2020)
Mathieu Carrière, Andrew J. Blumberg
Multiparameter Persistence Image for Topological Machine Learning. NeurIPS (2020)
Andrew Aukerman, Mathieu Carrière, Chao Chen, Kevin Gardner, Raúl Rabadán, Rami Vanguri
Persistent Homology Based Characterization of the Breast Cancer Immune Microenvironment: A Feasibility Study. SoCG (2020)
Mathieu Carrière, Frédéric Chazal, Yuichi Ike, Théo Lacombe, Martin Royer, Yuhei Umeda
PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures. AISTATS (2020)
Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan
A note on stochastic subgradient descent for persistence-based functionals: convergence and practical aspects. CoRR (2020)
Rachel Jeitziner, Mathieu Carrière, Jacques Rougemont, Steve Oudot, Kathryn Hess, Cathrin Brisken
Two-Tier Mapper, an unbiased topology-based clustering method for enhanced global gene expression analysis. Bioinform. 35 (18) (2019)
Mathieu Carrière, Ulrich Bauer
On the Metric Distortion of Embedding Persistence Diagrams into Separable Hilbert Spaces. SoCG (2019)
Mathieu Carrière, Frédéric Chazal, Yuichi Ike, Théo Lacombe, Martin Royer, Yuhei Umeda
A General Neural Network Architecture for Persistence Diagrams and Graph Classification. CoRR (2019)
Mathieu Carrière, Bertrand Michel
Approximation of Reeb spaces with Mappers and Applications to Stochastic Filters. CoRR (2019)
Mathieu Carrière, Steve Oudot
Structure and Stability of the One-Dimensional Mapper. Found. Comput. Math. 18 (6) (2018)
Mathieu Carrière, Bertrand Michel, Steve Oudot
Statistical Analysis and Parameter Selection for Mapper. J. Mach. Learn. Res. 19 (2018)
Mathieu Carrière, Raul Rabadan
Topological Data Analysis of Single-cell Hi-C Contact Maps. CoRR (2018)
Mathieu Carrière, Ulrich Bauer
On the Metric Distortion of Embedding Persistence Diagrams into Reproducing Kernel Hilbert Spaces. CoRR (2018)
Mathieu Carrière, Marco Cuturi, Steve Oudot
Sliced Wasserstein Kernel for Persistence Diagrams. ICML (2017)
Mathieu Carrière, Bertrand Michel, Steve Oudot
Statistical Analysis and Parameter Selection for Mapper. CoRR (2017)
Mathieu Carrière, Steve Oudot
Local Equivalence and Intrinsic Metrics between Reeb Graphs. CoRR (2017)
Mathieu Carrière, Marco Cuturi, Steve Oudot
Sliced Wasserstein Kernel for Persistence Diagrams. CoRR (2017)
Mathieu Carrière, Steve Oudot
Local Equivalence and Intrinsic Metrics between Reeb Graphs. SoCG (2017)
Mathieu Carrière, Steve Oudot
Structure and Stability of the 1-Dimensional Mapper. SoCG (2016)
Mathieu Carrière, Steve Y. Oudot, Maks Ovsjanikov
Stable Topological Signatures for Points on 3D Shapes. Comput. Graph. Forum 34 (5) (2015)
Mathieu Carrière, Steve Oudot
Structure and Stability of the 1-Dimensional Mapper. CoRR (2015)

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Publication Activity (10 Years)

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Mathieu Carrière