Topological Feature Extraction
Topological Feature Extraction is a computational methodology that identifies and quantifies invariant structural properties of data across different scales by leveraging tools from algebraic topology, particularly persistent homology, to reveal qualitative geometric patterns such as connected components, loops, and voids that persist under continuous deformations.
284
Publications
19.4K
Citations
869
Authors
411
Institutions
Publications per year
2017–2026
143
284
Boris Furtula, İvan Gutman · Journal of Mathematical Chemistry · 2015 · 970 citations
The Isomap Algorithm and Topological Stability
Mukund Balasubramanian, Eric L. Schwartz · Science · 2002 · 844 citations
Extracting insights from the shape of complex data using topology
Pek Yee Lum, Amy Lehman, T. Ishkanov et al. · Scientific Reports · 2013 · 544 citations · Full text
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Michigan State University
East Lansing, United States
11 h-index
29 publications
1.8K citations

Centre National de la Recherche Scientifique
Paris, France
8 h-index
17 publications
805 citations
University of California, Davis
Davis, United States
8 h-index
15 publications
1.2K citations
University of Oxford
Oxford, United Kingdom
6 h-index
16 publications
624 citations
University of Pennsylvania
Philadelphia, United States
6 h-index
12 publications
477 citations

Lawrence Berkeley National Laboratory
Berkeley, United States
5 h-index
14 publications
970 citations

Lawrence Livermore National Laboratory
Livermore, United States
5 h-index
13 publications
944 citations
Carnegie Mellon University
Pittsburgh, United States
5 h-index
17 publications
1.7K citations
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Repository · 13 publications · 504 citations
11
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TVCG · 7 publications · 518 citations
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4 publications · 3.4K citations
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4 publications · 172 citations
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PRB · 4 publications · 200 citations
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