Mathieu Carrière

According to our database, Mathieu Carrière authored at least 30 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2024

Differentiable Mapper For Topological Optimization Of Data Representation.

Ziyad Oulhaj, Mathieu Carrière, Bertrand Michel

CoRR, 2024

2023

A gradient sampling algorithm for stratified maps with applications to topological data analysis.

Jacob Leygonie, Mathieu Carrière, Théo Lacombe, Steve Oudot

Math. Program., November, 2023

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

Felix Hensel, Charles Arnal, Mathieu Carrière, Théo Lacombe, Hiroaki Kurihara, Yuichi Ike, Frédéric Chazal

CoRR, 2023

Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures.

David Loiseaux, Luis Scoccola, Mathieu Carrière, Magnus Bakke Botnan, Steve Oudot

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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

David Loiseaux, Mathieu Carrière, Andrew J. Blumberg

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Statistical analysis of Mapper for stochastic and multivariate filters.

Mathieu Carrière, Bertrand Michel

J. Appl. Comput. Topol., 2022

Efficient Approximation of Multiparameter Persistence Modules.

David Loiseaux, Mathieu Carrière, Andrew J. Blumberg

CoRR, 2022

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

Thibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frédéric Chazal

Proceedings of the Topological, 2022

2021

Topology identifies emerging adaptive mutations in SARS-CoV-2.

Michael Bleher, Lukas Hahn, Juan Ángel Patino-Galindo, Mathieu Carrière, Ulrich Bauer, Raul Rabadan, Andreas Ott

CoRR, 2021

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

Ewan Carr, Mathieu Carrière, Bertrand Michel, Frédéric Chazal, Raquel Iniesta

BMC Bioinform., 2021

Topological Uncertainty: Monitoring Trained Neural Networks through Persistence of Activation Graphs.

Théo Lacombe, Yuichi Ike, Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuhei Umeda

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Optimizing persistent homology based functions.

Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan, Yuhei Umeda

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

A note on stochastic subgradient descent for persistence-based functionals: convergence and practical aspects.

Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan

CoRR, 2020

MREC: a fast and versatile framework for aligning and matching point clouds with applications to single cell molecular data.

Andrew J. Blumberg, Mathieu Carrière, Michael A. Mandell, Raul Rabadan, Soledad Villar

CoRR, 2020

Multiparameter Persistence Image for Topological Machine Learning.

Mathieu Carrière, Andrew J. Blumberg

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Persistent Homology Based Characterization of the Breast Cancer Immune Microenvironment: A Feasibility Study.

Andrew Aukerman, Mathieu Carrière, Chao Chen, Kevin Gardner, Raúl Rabadán, Rami Vanguri

Proceedings of the 36th International Symposium on Computational Geometry, 2020

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

Mathieu Carrière, Frédéric Chazal, Yuichi Ike, Théo Lacombe, Martin Royer, Yuhei Umeda

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Approximation of Reeb spaces with Mappers and Applications to Stochastic Filters.

Mathieu Carrière, Bertrand Michel

CoRR, 2019

A General Neural Network Architecture for Persistence Diagrams and Graph Classification.

Mathieu Carrière, Frédéric Chazal, Yuichi Ike, Théo Lacombe, Martin Royer, Yuhei Umeda

CoRR, 2019

Two-Tier Mapper, an unbiased topology-based clustering method for enhanced global gene expression analysis.

Rachel Jeitziner, Mathieu Carrière, Jacques Rougemont, Steve Oudot, Kathryn Hess, Cathrin Brisken

Bioinform., 2019

On the Metric Distortion of Embedding Persistence Diagrams into Separable Hilbert Spaces.

Mathieu Carrière, Ulrich Bauer

Proceedings of the 35th International Symposium on Computational Geometry, 2019

2018

Statistical Analysis and Parameter Selection for Mapper.

Mathieu Carrière, Bertrand Michel, Steve Oudot

J. Mach. Learn. Res., 2018

Structure and Stability of the One-Dimensional Mapper.

Mathieu Carrière, Steve Oudot

Found. Comput. Math., 2018

Topological Data Analysis of Single-cell Hi-C Contact Maps.

Mathieu Carrière, Raul Rabadan

CoRR, 2018

On the Metric Distortion of Embedding Persistence Diagrams into Reproducing Kernel Hilbert Spaces.

Mathieu Carrière, Ulrich Bauer

CoRR, 2018

2017

On metric and statistical properties of topological descriptors for geometric data. (Sur les propriétés métriques et statistiques des descripteurs topologiques pour les données géométriques).

Mathieu Carrière

PhD thesis, 2017

Sliced Wasserstein Kernel for Persistence Diagrams.

Mathieu Carrière, Marco Cuturi, Steve Oudot

Proceedings of the 34th International Conference on Machine Learning, 2017

Local Equivalence and Intrinsic Metrics between Reeb Graphs.

Mathieu Carrière, Steve Oudot

Proceedings of the 33rd International Symposium on Computational Geometry, 2017

2016

Structure and Stability of the 1-Dimensional Mapper.

Mathieu Carrière, Steve Oudot

Proceedings of the 32nd International Symposium on Computational Geometry, 2016

2015

Stable Topological Signatures for Points on 3D Shapes.

Mathieu Carrière, Steve Y. Oudot, Maks Ovsjanikov

Comput. Graph. Forum, 2015