Mathieu Carrière

Orcid: 0000-0002-4747-9915

According to our database1, Mathieu Carrière authored at least 34 papers between 2015 and 2024.

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Bibliography

2024
MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Neural Networks.
Trans. Mach. Learn. Res., 2024

Resampling and averaging coordinates on data.
CoRR, 2024

Diffeomorphic interpolation for efficient persistence-based topological optimization.
CoRR, 2024

Differentiability and Optimization of Multiparameter Persistent Homology.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Differentiable Mapper for Topological Optimization of Data Representation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
A gradient sampling algorithm for stratified maps with applications to topological data analysis.
Math. Program., November, 2023

MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks.
CoRR, 2023

Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures.
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.
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.
J. Appl. Comput. Topol., 2022

Efficient Approximation of Multiparameter Persistence Modules.
CoRR, 2022

RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds.
Proceedings of the Topological, 2022

2021
Topology identifies emerging adaptive mutations in SARS-CoV-2.
CoRR, 2021

Identifying homogeneous subgroups of patients and important features: a topological machine learning approach.
BMC Bioinform., 2021

Topological Uncertainty: Monitoring Trained Neural Networks through Persistence of Activation Graphs.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Optimizing persistent homology based functions.
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.
CoRR, 2020

MREC: a fast and versatile framework for aligning and matching point clouds with applications to single cell molecular data.
CoRR, 2020

Multiparameter Persistence Image for Topological Machine Learning.
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.
Proceedings of the 36th International Symposium on Computational Geometry, 2020

PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Approximation of Reeb spaces with Mappers and Applications to Stochastic Filters.
CoRR, 2019

A General Neural Network Architecture for Persistence Diagrams and Graph Classification.
CoRR, 2019

Two-Tier Mapper, an unbiased topology-based clustering method for enhanced global gene expression analysis.
Bioinform., 2019

On the Metric Distortion of Embedding Persistence Diagrams into Separable Hilbert Spaces.
Proceedings of the 35th International Symposium on Computational Geometry, 2019

2018
Statistical Analysis and Parameter Selection for Mapper.
J. Mach. Learn. Res., 2018

Structure and Stability of the One-Dimensional Mapper.
Found. Comput. Math., 2018

Topological Data Analysis of Single-cell Hi-C Contact Maps.
CoRR, 2018

On the Metric Distortion of Embedding Persistence Diagrams into Reproducing Kernel Hilbert Spaces.
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).
PhD thesis, 2017

Sliced Wasserstein Kernel for Persistence Diagrams.
Proceedings of the 34th International Conference on Machine Learning, 2017

Local Equivalence and Intrinsic Metrics between Reeb Graphs.
Proceedings of the 33rd International Symposium on Computational Geometry, 2017

2016
Structure and Stability of the 1-Dimensional Mapper.
Proceedings of the 32nd International Symposium on Computational Geometry, 2016

2015
Stable Topological Signatures for Points on 3D Shapes.
Comput. Graph. Forum, 2015


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