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Persistent homology (PH) is a rigorous mathematical theory that provides a robust descriptor of data in the form of persistence diagrams (PDs) which are 2D multisets of points. Their variable size makes them, however, difficult to combine…

Machine Learning · Statistics 2019-06-14 Bartosz Zielinski , Michal Lipinski , Mateusz Juda , Matthias Zeppelzauer , Pawel Dlotko

We investigate combinatorial dynamical systems on simplicial complexes considered as {\em finite topological spaces}. Such systems arise in a natural way from sampling dynamics and may be used to reconstruct some features of the dynamics…

Algebraic Topology · Mathematics 2018-07-12 Tamal K. Dey , Mateusz Juda , Tomasz Kapela , Jacek Kubica , Michal Lipinski , Marian Mrozek

We study the persistent homology of both functional data on compact topological spaces and structural data presented as compact metric measure spaces. One of our goals is to define persistent homology so as to capture primarily properties…

Algebraic Topology · Mathematics 2018-11-27 Haibin Hang , Facundo Mémoli , Washington Mio

Persistent Homology is a powerful tool in Topological Data Analysis (TDA) to capture topological properties of data succinctly at different spatial resolutions. For graphical data, shape, and structure of the neighborhood of individual data…

Social and Information Networks · Computer Science 2018-11-12 Sumit Bhatia , Bapi Chatterjee , Deepak Nathani , Manohar Kaul

We give bounds for dimension 0 persistent homology and codimension 1 homology of Vietoris--Rips, alpha, and cubical complex filtrations from finite sets related by enrichment (adding new elements), sparsification (removing elements), and…

Algebraic Topology · Mathematics 2025-12-05 Jānis Lazovskis , Ran Levi , Juliano Morimoto

Topological Data Analysis (TDA) is a rising field of computational topology in which the topological structure of a data set can be observed by persistent homology. By considering a sequence of sublevel sets, one obtains a filtration that…

Methodology · Statistics 2020-03-17 Yu-Min Chung , William Cruse , Austin Lawson

The combinatorial interpretation of the persistence diagram as a M\"obius inversion was recently shown to be functorial. We employ this discovery to recast the Persistent Homology Transform of a geometric complex as a representation of a…

Algebraic Topology · Mathematics 2024-05-16 Brittany Terese Fasy , Amit Patel

We first want to consider the formal deformation of a fibered manifold $P \rightarrow M$ as a (bi-)module or subalgebra, where $M$ has a given differential star product. Consequently we want to find obstructions for the existence of a…

Quantum Algebra · Mathematics 2018-06-05 Benedikt Hurle

Let $K$ be a finite simplicial, cubical, delta or CW complex. The persistence map $\mathrm{PH}$ takes a filter $f:K \rightarrow \mathbb{R}$ as input and returns the barcodes $\mathrm{PH}(f)$ of the associated sublevel set persistent…

Computational Geometry · Computer Science 2021-10-29 Jacob Leygonie , Gregory Henselman-Petrusek

In medical image analysis, feature engineering plays an important role in the design and performance of machine learning models. Persistent homology (PH), from the field of topological data analysis (TDA), demonstrates robustness and…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Dashti A. Ali , Richard K. G. Do , William R. Jarnagin , Aras T. Asaad , Amber L. Simpson

Recently, multi-scale notions of local homology (a variant of persistent homology) have been used to study the local structure of spaces around a given point from a point cloud sample. Current reconstruction guarantees rely on constructing…

Computational Geometry · Computer Science 2013-04-24 Primoz Skraba , Bei Wang

Persistent homology is an important methodology in topological data analysis which adapts theory from algebraic topology to data settings. Computing persistent homology produces persistence diagrams, which have been successfully used in…

Machine Learning · Statistics 2026-01-13 Yueqi Cao , Anthea Monod

Topological data analysis (TDA) is an area of data science that focuses on using invariants from algebraic topology to provide multiscale shape descriptors for geometric data sets such as point clouds. One of the most important such…

Computational Geometry · Computer Science 2023-06-21 David Loiseaux , Mathieu Carrière , Andrew J. Blumberg

The persistent homology of a stationary point process on ${\bf R}^N$ is studied in this paper. As a generalization of continuum percolation theory, we study higher dimensional topological features of the point process such as loops,…

Probability · Mathematics 2016-12-28 Trinh Khanh Duy , Yasuaki Hiraoka , Tomoyuki Shirai

Features such as photon rings, jets, or hot. spots can leave particular topological signatures in a black hole image. As such, topological data analysis can be used to characterize images resulting from high resolution observations…

High Energy Astrophysical Phenomena · Physics 2022-10-11 Pierre Christian , Chi-kwan Chan , Anthony Hsu , Feryal Ozel , Dimitrios Psaltis , Iniyan Natarajan

Persistent homology provides information about the lifetime of homology classes along a filtration of cell complexes. Persistence barcode is a graphical representation of such information. A filtration might be determined by time in a set…

Computer Vision and Pattern Recognition · Computer Science 2018-01-04 Rocio Gonzalez-Diaz , Maria-Jose Jimenez , Belen Medrano

In this work we consider the Gutt star product viewed as an associative deformation of the symmetric algebra S^\bullet(g) over a Lie algebra g and discuss its continuity properties: we establish a locally convex topology on S^\bullet(g)…

Quantum Algebra · Mathematics 2017-03-24 Chiara Esposito , Paul Stapor , Stefan Waldmann

In this article we consider quantum phase space reduction when zero is a regular value of the momentum map. By analogy with the classical case we define the BRST cohomology in the framework of deformation quantization. We compute the…

Quantum Algebra · Mathematics 2014-11-18 Martin Bordemann , Hans-Christian Herbig , Stefan Waldmann

Persistent homology (PH) provides topological descriptors for geometric data, such as weighted graphs, which are interpretable, stable to perturbations, and invariant under, e.g., relabeling. Most applications of PH focus on the…

Machine Learning · Computer Science 2024-02-08 David Loiseaux , Luis Scoccola , Mathieu Carrière , Magnus Bakke Botnan , Steve Oudot

We discuss and review recent developments in the area of applied algebraic topology, such as persistent homology and barcodes. In particular, we discuss how these are related to understanding more about manifold learning from random point…

Probability · Mathematics 2015-03-13 Robert J. Adler , Omer Bobrowski , Matthew S. Borman , Eliran Subag , Shmuel Weinberger
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