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	RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds Felix Hensel , Marc Glisse , Frédéric Chazal , Thibault de Surrel , Mathieu Carriere Proceedings of Machine Learning Research, 2022, Proceedings of Topological, Algebraic, and Geometric Learning Workshops 2022, 196, pp.96-106 Article dans une revue hal-03867083v1

	RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds Thibault de Surrel , Felix Hensel , Mathieu Carriere , Théo Lacombe , Yuichi Ike ICLR 2022 Workshop on Geometrical and Topological Representation Learning, Apr 2022, Virtual conference, United States Communication dans un congrès hal-03560450v1
	Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs Théo Lacombe , Yuichi Ike , Mathieu Carriere , Frédéric Chazal , Marc Glisse IJCAI 2021 - 30th International Joint Conference on Artificial Intelligence, Aug 2021, Montréal, Canada. pp.2666-2672, ⟨10.24963/ijcai.2021/367⟩ Communication dans un congrès hal-03213188v1
	Optimizing persistent homology based functions Mathieu Carriere , Frédéric Chazal , Marc Glisse , Yuichi Ike , Hariprasad Kannan ICML 2021 - 38th International Conference on Machine Learning, Jul 2021, Virtual conference, United States. pp.1294-1303 Communication dans un congrès hal-02969305v2

Marc Glisse