Comparing persistence diagrams through complex vectors
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Abstract (arXiv)
The natural pseudo-distance of spaces endowed with filtering functions is precious for shape classification and retrieval; its optimal estimate coming from persistence diagrams is the bottleneck distance, which unfortunately suffers from combinatorial explosion. A possible algebraic representation of persistence diagrams is offered by complex polynomials; since far polynomials represent far persistence diagrams, a fast comparison of the coefficient vectors can reduce the size of the database to be classified by the bottleneck distance. This article explores experimentally three transformations from diagrams to polynomials and three distances between the complex vectors of coefficients.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 May 2015.
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Citing papers per year: 2021: 3; 2022: 3; 2023: 0; 2024: 0; 2025: 1; 2026: 2.
9 papers.
- 2022Predicting the generalization gap in neural networks using topological data analysiscited by 9
- 2022Approximating Persistent Homology for Large Datasetscited by 8
- 2021Learning Hyperbolic Representations of Topological Featurescited by 7
- 2021Topology Applied to Machine Learning: From Global to Localcited by 4
- 2021Smart Vectorizations for Single and Multiparameter Persistencecited by 1
- 2026Fixation Sequences as Time Series: A Topological Approach to Dyslexia Detectioncited by 1
- 2022Convolutional Persistence Transformscited by 0
- 2025Persistence Spheres: Bi-continuous Representations of Persistence Diagramscited by 0
- 2026Voronoi Histograms for Adaptive Vectorization of Expected Persistence Diagramscited by 0
- 2026Voronoi Histograms for Adaptive Vectorization of Expected Persistence Diagrams29 Jul 2026
- 2026Fixation Sequences as Time Series: A Topological Approach to Dyslexia Detection23 Apr 2026
- 2025Persistence Spheres: Bi-continuous Representations of Persistence Diagrams21 Sep 2025
- 2022Convolutional Persistence Transforms3 Aug 2022
- 2022Approximating Persistent Homology for Large Datasets19 Apr 2022
- 2022Predicting the generalization gap in neural networks using topological data analysis23 Mar 2022
- 2021Smart Vectorizations for Single and Multiparameter Persistence10 Apr 2021
- 2021Learning Hyperbolic Representations of Topological Features16 Mar 2021
- 2021Topology Applied to Machine Learning: From Global to Local10 Mar 2021