Mathieu Carrière

发表

Sliced Wasserstein Kernel for Persistence Diagrams

Steve Oudot, Mathieu Carrière, Marco Cuturi, 2017, ICML.

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

Michael A. Mandell, A. Blumberg, R. Rabadán, 2020, ArXiv.

Efficient Approximation of Multiparameter Persistence Modules

A. Blumberg, Mathieu Carrière, David Loiseaux, 2022, ArXiv.

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

Steve Oudot, Mathieu Carrière, Jacques Rougemont, 2019, Bioinform..

Two-Tier Mapper: a user-independent clustering method for global gene expression analysis based on topology

Steve Oudot, Kathryn Hess, Mathieu Carriere, 2017, 1801.01841.

PersLay: A Simple and Versatile Neural Network Layer for Persistence Diagrams

F. Chazal, Théo Lacombe, Mathieu Carrière, 2019 .

Eurographics Symposium on Geometry Processing 2015 Stable Topological Signatures for Points on 3d Shapes

Steve Oudot, Maks Ovsjanikov, Mathieu Carrière, 2022 .

Topological data analysis identifies emerging adaptive mutations in SARS-CoV-2

J. A. Patino-Galindo, R. Rabadán, Mathieu Carrière, 2021, 2106.07292.

Supplementary Material for "Multiparameter Persistence Image for Topological Machine Learning"

Mathieu Carrière, Andrew J. Blumberg, 2020 .

Multiparameter Persistence Image for Topological Machine Learning

Andrew J. Blumberg, Mathieu Carrière, A. Blumberg, 2020, NeurIPS.

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

Mathieu Carrière, Andrew Aukerman, Rami Vanguri, 2020, SoCG.

Statistical analysis of Mapper for stochastic and multivariate filters

Mathieu Carrière, B. Michel, 2022, Journal of Applied and Computational Topology.

Statistical analysis of Mapper for stochastic and multivariate filters

Mathieu Carrière, B. Michel, 2022, J. Appl. Comput. Topol..

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

Ulrich Bauer, Mathieu Carrière, U. Bauer, 2018, ArXiv.

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

F. Chazal, Théo Lacombe, Mathieu Carrière, 2019, AISTATS.

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

Mathieu Carrière, Raul Rabadan, R. Rabadán, 2018, bioRxiv.

Statistical Analysis and Parameter Selection for Mapper

Steve Oudot, Mathieu Carrière, Bertrand Michel, 2017, J. Mach. Learn. Res..

Structure and Stability of the One-Dimensional Mapper

Steve Oudot, Mathieu Carrière, S. Oudot, 2015, Found. Comput. Math..

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

Soledad Villar, Raul Rabadan, Andrew J. Blumberg, 2020 .

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

A. Blumberg, Mathieu Carrière, David Loiseaux, 2023, NeurIPS.

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

Ulrich Bauer, Mathieu Carrière, Mathieu Carrière, 2018, SoCG.

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

F. Chazal, M. Glisse, Théo Lacombe, 2022, TAG-ML.

Stable Topological Signatures for Points on 3D Shapes

M. Ovsjanikov, S. Oudot, Mathieu Carrière, 2015, Eurographics Symposium on Geometry Processing.

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

Frédéric Chazal, Mathieu Carrière, Yuichi Ike, 2019, ArXiv.

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, Mathieu Carrière, 2017 .

Local Signatures using Persistence Diagrams

Steve Oudot, Maks Ovsjanikov, Mathieu Carrière, 2015 .

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

Steve Oudot, Mathieu Carriere, Jacob Leygonie, 2021, Mathematical Programming.

Optimizing persistent homology based functions

Frédéric Chazal, Marc Glisse, Mathieu Carrière, 2020, ICML.

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

Marc Glisse, Yuichi Ike, Hariprasad Kannan, 2020, ArXiv.

Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures

S. Oudot, M. B. Botnan, Mathieu Carrière, 2023, ArXiv.

Topological data analysis identifies emerging adaptive mutations in SARS-CoV-2 (preprint)/ en

J. A. Patino-Galindo, R. Rabadán, Mathieu Carrière, 2021, 2106.07292.

Fast, Stable and Efficient Approximation of Multi-parameter Persistence Modules with MMA

A. Blumberg, Mathieu Carrière, David Loiseaux, 2022, 2206.02026.

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

Frédéric Chazal, Mathieu Carrière, Bertrand Michel, 2021, BMC Bioinform..

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

Bertrand Michel, Mathieu Carriere, Mathieu Carrière, 2019, ArXiv.

Structure and Stability of the One-Dimensional Mapper

S. Oudot, Mathieu Carrière, 2017, Foundations of Computational Mathematics.

Local Equivalence and Intrinsic Metrics between Reeb Graphs pdf

Steve Oudot, Mathieu Carrière, S. Oudot, 2017, SoCG.

Structure and Stability of the 1-Dimensional Mapper

Steve Oudot, Mathieu Carrière, S. Oudot, 2016, SoCG.

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

F. Chazal, Théo Lacombe, Mathieu Carrière, 2023, ArXiv.

Multiparameter Persistence Images for Topological Machine Learning

A. Blumberg, Mathieu Carrière, 2020 .