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
Diffeomorphic interpolation for efficient persistence-based topological optimization.
CoRR, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
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
J. Appl. Comput. Topol., 2022
RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds.
Proceedings of the Topological, 2022
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
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
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
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
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
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the 33rd International Symposium on Computational Geometry, 2017
2016
Proceedings of the 32nd International Symposium on Computational Geometry, 2016
2015