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

Thibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frédéric Chazal. RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds. In Alexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf, editors, Topological, Algebraic and Geometric Learning Workshops 2022, 25-22 July 2022, Virtual. Volume 196 of Proceedings of Machine Learning Research, pages 96-106, PMLR, 2022. [doi]

@inproceedings{SurrelHCLIKGC22,
  title = {RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds},
  author = {Thibault de Surrel and Felix Hensel and Mathieu Carrière and Théo Lacombe and Yuichi Ike and Hiroaki Kurihara and Marc Glisse and Frédéric Chazal},
  year = {2022},
  url = {https://proceedings.mlr.press/v196/surrel22a.html},
  researchr = {https://researchr.org/publication/SurrelHCLIKGC22},
  cites = {0},
  citedby = {0},
  pages = {96-106},
  booktitle = {Topological, Algebraic and Geometric Learning Workshops 2022, 25-22 July 2022, Virtual},
  editor = {Alexander Cloninger and Timothy Doster and Tegan Emerson and Manohar Kaul and Ira Ktena and Henry Kvinge and Nina Miolane and Bastian Rice and Sarah Tymochko and Guy Wolf},
  volume = {196},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
}