Lattice Paths for Persistent Diagrams
Not on the map. Why?
Abstract (arXiv)
Persistent homology has undergone significant development in recent years. However, one outstanding challenge is to build a coherent statistical inference procedure on persistent diagrams. In this paper, we first present a new lattice path representation for persistent diagrams. We then develop a new exact statistical inference procedure for lattice paths via combinatorial enumerations. The lattice path method is applied to the topological characterization of the protein structures of the COVID-19 virus. We demonstrate that there are topological changes during the conformational change of spike proteins.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 30 references that are in the map. First posted on arXiv 1 May 2021.
Builds on
4 of 30 references.
References · 4
- 2013On the Bootstrap for Persistence Diagrams and Landscapescited by 7
- 2020Smile-GANs: Semi-supervised clustering via GANs for dissecting brain disease heterogeneity from medical imagescited by 4
- 2014Persistent Homology in Sparse Regression and its Application to Brain Morphometrycited by 3
- 2018Exact Combinatorial Inference for Brain Imagescited by 1
Built on by
Not cited yet.