Persistence paths and signature features in topological data analysis
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Abstract (arXiv)
We introduce a new feature map for barcodes that arise in persistent homology computation. The main idea is to first realize each barcode as a path in a convenient vector space, and to then compute its path signature which takes values in the tensor algebra of that vector space. The composition of these two operations - barcode to path, path to tensor series - results in a feature map that has several desirable properties for statistical learning, such as universality and characteristicness, and achieves state-of-the-art results on common classification benchmarks.
Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Jun 2018.
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Citing papers per year: 2021: 4; 2022: 3; 2023: 4; 2024: 1; 2025: 3; 2026: 2.
17 papers.
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- 2021Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutionscited by 38
- 2023Topological Deep Learning: A Review of an Emerging Paradigmcited by 34
- 2023PCF-GAN: generating sequential data via the characteristic function of measures on the path spacecited by 13
- 2021Cycle Registration in Persistent Homology with Applications in Topological Bootstrapcited by 8
- 2022Approximating Persistent Homology for Large Datasetscited by 8
- 2022Euler Characteristic Curves and Profiles: a stable shape invariant for big data problemscited by 8
- 2023The Signature Kernelcited by 8
- 2021Feature Engineering with Regularity Structurescited by 7
- 20222-d signature of images and texture classificationcited by 2
- 2023FRUITS: Feature Extraction Using Iterated Sums for Time Series Classificationcited by 1
- 2025Comparing the Effects of Persistence Barcodes Aggregation and Feature Concatenation on Medical Imagingcited by 1
- 2025Global universal approximation with Brownian signaturescited by 1
5 more
- 2021From augmented microscopy to the topological transformer: a new approach in cell image analysis for Alzheimer's researchcited by 0
- 2024A Vectorization Method Induced By Maximal Margin Classification For Persistent Diagramscited by 0
- 2025A Novel Patch-Based TDA Approach for Computed Tomography Imagingcited by 0
- 2026Global universality via discrete-time signaturescited by 0
- 2026Voronoi Histograms for Adaptive Vectorization of Expected Persistence Diagramscited by 0
- 2026Voronoi Histograms for Adaptive Vectorization of Expected Persistence Diagrams29 Jul 2026
- 2026Global universality via discrete-time signatures10 Mar 2026
- 2025Global universal approximation with Brownian signatures18 Dec 2025
- 2025A Novel Patch-Based TDA Approach for Computed Tomography Imaging13 Dec 2025
- 2025Comparing the Effects of Persistence Barcodes Aggregation and Feature Concatenation on Medical Imaging29 May 2025
- 2024A Vectorization Method Induced By Maximal Margin Classification For Persistent Diagrams31 Jul 2024
- 2023FRUITS: Feature Extraction Using Iterated Sums for Time Series Classification24 Nov 2023
- 2023PCF-GAN: generating sequential data via the characteristic function of measures on the path space21 May 2023
- 2023The Signature Kernel8 May 2023
- 2023Topological Deep Learning: A Review of an Emerging Paradigm8 Feb 2023
- 2022Euler Characteristic Curves and Profiles: a stable shape invariant for big data problems3 Dec 2022
- 20222-d signature of images and texture classification10 May 2022
5 more
- 2022Approximating Persistent Homology for Large Datasets19 Apr 2022
- 2021Feature Engineering with Regularity Structures12 Aug 2021
- 2021From augmented microscopy to the topological transformer: a new approach in cell image analysis for Alzheimer's research3 Aug 2021
- 2021Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions2 Jun 2021
- 2021Cycle Registration in Persistent Homology with Applications in Topological Bootstrap3 Jan 2021
- 2021Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutionscited by 38
- 2023Topological Deep Learning: A Review of an Emerging Paradigmcited by 34
- 2023PCF-GAN: generating sequential data via the characteristic function of measures on the path spacecited by 13
- 2021Cycle Registration in Persistent Homology with Applications in Topological Bootstrapcited by 8
- 2022Approximating Persistent Homology for Large Datasetscited by 8
- 2022Euler Characteristic Curves and Profiles: a stable shape invariant for big data problemscited by 8
- 2023The Signature Kernelcited by 8
- 2021Feature Engineering with Regularity Structurescited by 7
- 20222-d signature of images and texture classificationcited by 2
- 2023FRUITS: Feature Extraction Using Iterated Sums for Time Series Classificationcited by 1
- 2025Comparing the Effects of Persistence Barcodes Aggregation and Feature Concatenation on Medical Imagingcited by 1
- 2025Global universal approximation with Brownian signaturescited by 1
12 most cited of 17 All 17 (JSON)
- 2026Voronoi Histograms for Adaptive Vectorization of Expected Persistence Diagrams29 Jul 2026
- 2026Global universality via discrete-time signatures10 Mar 2026
- 2025Global universal approximation with Brownian signatures18 Dec 2025
- 2025A Novel Patch-Based TDA Approach for Computed Tomography Imaging13 Dec 2025
- 2025Comparing the Effects of Persistence Barcodes Aggregation and Feature Concatenation on Medical Imaging29 May 2025
- 2024A Vectorization Method Induced By Maximal Margin Classification For Persistent Diagrams31 Jul 2024
- 2023FRUITS: Feature Extraction Using Iterated Sums for Time Series Classification24 Nov 2023
- 2023PCF-GAN: generating sequential data via the characteristic function of measures on the path space21 May 2023
- 2023The Signature Kernel8 May 2023
- 2023Topological Deep Learning: A Review of an Emerging Paradigm8 Feb 2023
- 2022Euler Characteristic Curves and Profiles: a stable shape invariant for big data problems3 Dec 2022
- 20222-d signature of images and texture classification10 May 2022
12 newest of 17 All 17 (JSON)