• Corpus ID: 17162382

Persistence Images: A Stable Vector Representation of Persistent Homology

@article{Adams2017PersistenceIA,
  title={Persistence Images: A Stable Vector Representation of Persistent Homology},
  author={Henry Adams and Tegan H. Emerson and Michael J. Kirby and Rachel Neville and Chris Peterson and Patrick D. Shipman and Sofya Chepushtanova and Eric M. Hanson and Francis C. Motta and Lori Ziegelmeier},
  journal={J. Mach. Learn. Res.},
  year={2017},
  volume={18},
  pages={8:1-8:35}
}
Many datasets can be viewed as a noisy sampling of an underlying space, and tools from topological data analysis can characterize this structure for the purpose of knowledge discovery. One such tool is persistent homology, which provides a multiscale description of the homological features within a dataset. A useful representation of this homological information is a persistence diagram (PD). Efforts have been made to map PDs into spaces with additional structure valuable to machine learning… 
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