Mathieu Carrière

52 papers A* 14A 1Journal 35Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Persistence-based topological optimization: a survey. CoRR Mathieu Carrière, Yuichi Ike, Théo Lacombe, Naoki Nishikawa
2025	J	`jnl`	Multi-parameter Module Approximation: an efficient and interpretable invariant for multi-parameter persistence modules with guarantees. J. Appl. Comput. Topol. David Loiseaux, Mathieu Carrière, Andrew J. Blumberg
2025	A*	`conf`	Sparsification of the Generalized Persistence Diagrams for Scalability Through Gradient Descent. SoCG Mathieu Carrière, Seunghyun Kim, Woojin Kim
2024	A*	`conf`	Diffeomorphic interpolation for efficient persistence-based topological optimization. NeurIPS Mathieu Carrière, Marc Theveneau, Théo Lacombe
2024	J	`jnl`	Diffeomorphic interpolation for efficient persistence-based topological optimization. CoRR Mathieu Carrière, Marc Theveneau, Théo Lacombe
2024	A*	`conf`	Differentiability and Optimization of Multiparameter Persistent Homology. ICML Luis Scoccola, Siddharth Setlur, David Loiseaux, Mathieu Carrière, Steve Oudot
2024	J	`jnl`	Differentiability and Optimization of Multiparameter Persistent Homology. CoRR Luis Scoccola, Siddharth Setlur, David Loiseaux, Mathieu Carrière, Steve Oudot
2024	J	`jnl`	Differentiable Mapper For Topological Optimization Of Data Representation. CoRR Ziyad Oulhaj, Mathieu Carrière, Bertrand Michel
2024	A*	`conf`	Differentiable Mapper for Topological Optimization of Data Representation. ICML Ziyad Oulhaj, Mathieu Carrière, Bertrand Michel
2024	J	`jnl`	MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Neural Networks. Trans. Mach. Learn. Res. Charles Arnal, Felix Hensel, Mathieu Carrière, Théo Lacombe, Hiroaki Kurihara, Yuichi Ike, Frédéric Chazal
2024	J	`jnl`	Resampling and averaging coordinates on data. CoRR Andrew J. Blumberg, Mathieu Carrière, Jun Hou Fung, Michael A. Mandell
2024	J	`jnl`	Sparsification of the Generalized Persistence Diagrams for Scalability through Gradient Descent. CoRR Mathieu Carrière, Seunghyun Kim, Woojin Kim
2024	J	`jnl`	Subsampling, aligning, and averaging to find circular coordinates in recurrent time series. CoRR Andrew J. Blumberg, Mathieu Carrière, Jun Hou Fung, Michael A. Mandell
2023	A*	`conf`	A Framework for Fast and Stable Representations of Multiparameter Persistent Homology Decompositions. NeurIPS David Loiseaux, Mathieu Carrière, Andrew J. Blumberg
2023	J	`jnl`	A Framework for Fast and Stable Representations of Multiparameter Persistent Homology Decompositions. CoRR David Loiseaux, Mathieu Carrière, Andrew J. Blumberg
2023	J	`jnl`	A gradient sampling algorithm for stratified maps with applications to topological data analysis. Math. Program. Jacob Leygonie, Mathieu Carrière, Théo Lacombe, Steve Oudot
2023	J	`jnl`	MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks. CoRR Felix Hensel, Charles Arnal, Mathieu Carrière, Théo Lacombe, Hiroaki Kurihara, Yuichi Ike, Frédéric Chazal
2023	A*	`conf`	Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures. NeurIPS David Loiseaux, Luis Scoccola, Mathieu Carrière, Magnus Bakke Botnan, Steve Oudot
2023	J	`jnl`	Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures. CoRR David Loiseaux, Luis Scoccola, Mathieu Carrière, Magnus Bakke Botnan, Steve Oudot
2022	J	`jnl`	Efficient Approximation of Multiparameter Persistence Modules. CoRR David Loiseaux, Mathieu Carrière, Andrew J. Blumberg
2022	—	`conf`	RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds. TAG-ML Thibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frédéric Chazal
2022	J	`jnl`	RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds. CoRR Thibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frédéric Chazal
2022	J	`jnl`	Statistical analysis of Mapper for stochastic and multivariate filters. J. Appl. Comput. Topol. Mathieu Carrière, Bertrand Michel
2021	J	`jnl`	A Gradient Sampling Algorithm for Stratified Maps with Applications to Topological Data Analysis. CoRR Jacob Leygonie, Mathieu Carrière, Théo Lacombe, Steve Oudot
2021	J	`jnl`	Identifying homogeneous subgroups of patients and important features: a topological machine learning approach. BMC Bioinform. Ewan Carr, Mathieu Carrière, Bertrand Michel, Frédéric Chazal, Raquel Iniesta
2021	A*	`conf`	Optimizing persistent homology based functions. ICML Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan, Yuhei Umeda
2021	J	`jnl`	Persistent homology based characterization of the breast cancer immune microenvironment: a feasibility study. J. Comput. Geom. Andrew Aukerman, Mathieu Carrière, Chao Chen, Kevin Gardner, Raúl Rabadán, Rami Vanguri
2021	A*	`conf`	Topological Uncertainty: Monitoring Trained Neural Networks through Persistence of Activation Graphs. IJCAI Théo Lacombe, Yuichi Ike, Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuhei Umeda
2021	J	`jnl`	Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs. CoRR Théo Lacombe, Yuichi Ike, Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuhei Umeda
2021	J	`jnl`	Topology identifies emerging adaptive mutations in SARS-CoV-2. CoRR Michael Bleher, Lukas Hahn, Juan Ángel Patino-Galindo, Mathieu Carrière, Ulrich Bauer, Raul Rabadan, Andreas Ott
2020	J	`jnl`	A note on stochastic subgradient descent for persistence-based functionals: convergence and practical aspects. CoRR Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan
2020	J	`jnl`	MREC: a fast and versatile framework for aligning and matching point clouds with applications to single cell molecular data. CoRR Andrew J. Blumberg, Mathieu Carrière, Michael A. Mandell, Raul Rabadan, Soledad Villar
2020	A*	`conf`	Multiparameter Persistence Image for Topological Machine Learning. NeurIPS Mathieu Carrière, Andrew J. Blumberg
2020	A	`conf`	PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures. AISTATS Mathieu Carrière, Frédéric Chazal, Yuichi Ike, Théo Lacombe, Martin Royer, Yuhei Umeda
2020	A*	`conf`	Persistent Homology Based Characterization of the Breast Cancer Immune Microenvironment: A Feasibility Study. SoCG Andrew Aukerman, Mathieu Carrière, Chao Chen, Kevin Gardner, Raúl Rabadán, Rami Vanguri
2019	J	`jnl`	A General Neural Network Architecture for Persistence Diagrams and Graph Classification. CoRR Mathieu Carrière, Frédéric Chazal, Yuichi Ike, Théo Lacombe, Martin Royer, Yuhei Umeda
2019	J	`jnl`	Approximation of Reeb spaces with Mappers and Applications to Stochastic Filters. CoRR Mathieu Carrière, Bertrand Michel
2019	A*	`conf`	On the Metric Distortion of Embedding Persistence Diagrams into Separable Hilbert Spaces. SoCG Mathieu Carrière, Ulrich Bauer
2019	J	`jnl`	Two-Tier Mapper, an unbiased topology-based clustering method for enhanced global gene expression analysis. Bioinform. Rachel Jeitziner, Mathieu Carrière, Jacques Rougemont, Steve Oudot, Kathryn Hess, Cathrin Brisken
2018	J	`jnl`	On the Metric Distortion of Embedding Persistence Diagrams into Reproducing Kernel Hilbert Spaces. CoRR Mathieu Carrière, Ulrich Bauer
2018	J	`jnl`	Statistical Analysis and Parameter Selection for Mapper. J. Mach. Learn. Res. Mathieu Carrière, Bertrand Michel, Steve Oudot
2018	J	`jnl`	Structure and Stability of the One-Dimensional Mapper. Found. Comput. Math. Mathieu Carrière, Steve Oudot
2018	J	`jnl`	Topological Data Analysis of Single-cell Hi-C Contact Maps. CoRR Mathieu Carrière, Raul Rabadan
2017	A*	`conf`	Local Equivalence and Intrinsic Metrics between Reeb Graphs. SoCG Mathieu Carrière, Steve Oudot
2017	J	`jnl`	Local Equivalence and Intrinsic Metrics between Reeb Graphs. CoRR Mathieu Carrière, Steve Oudot
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
2017	A*	`conf`	Sliced Wasserstein Kernel for Persistence Diagrams. ICML Mathieu Carrière, Marco Cuturi, Steve Oudot
2017	J	`jnl`	Sliced Wasserstein Kernel for Persistence Diagrams. CoRR Mathieu Carrière, Marco Cuturi, Steve Oudot
2017	J	`jnl`	Statistical Analysis and Parameter Selection for Mapper. CoRR Mathieu Carrière, Bertrand Michel, Steve Oudot
2016	A*	`conf`	Structure and Stability of the 1-Dimensional Mapper. SoCG Mathieu Carrière, Steve Oudot
2015	J	`jnl`	Stable Topological Signatures for Points on 3D Shapes. Comput. Graph. Forum Mathieu Carrière, Steve Y. Oudot, Maks Ovsjanikov
2015	J	`jnl`	Structure and Stability of the 1-Dimensional Mapper. CoRR Mathieu Carrière, Steve Oudot