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We redevelop persistent homology (topological persistence) from a categorical point of view. The main objects of study are diagrams, indexed by the poset of real numbers, in some target category. The set of such diagrams has an interleaving…

Algebraic Topology · Mathematics 2014-05-13 Peter Bubenik , Jonathan A. Scott

Persistent homology (PH) studies the topology of data across multiple scales by building nested collections of topological spaces called filtrations, computing homology and returning an algebraic object that can be vizualised as a…

Algebraic Topology · Mathematics 2024-11-14 David Beers , Heather A Harrington , Jacob Leygonie , Uzu Lim , Louis Theran

This paper introduces a method to detect each geometrically significant loop that is a geodesic circle (an isometric embedding of $S^1$) and a bottleneck loop (meaning that each of its perturbations increases the length) in a geodesic space…

Algebraic Topology · Mathematics 2024-11-13 Žiga Virk

A crucial step in the analysis of persistent homology is the transformation of data into an appropriate topological object (in our case, a simplicial complex). Modern packages for persistent homology often construct Vietoris--Rips or other…

Computational Geometry · Computer Science 2019-09-18 Michelle Feng , Mason A. Porter

Computational topology provides a tool, persistent homology, to extract quantitative descriptors from structured objects (images, graphs, point clouds, etc). These descriptors can then be involved in optimization problems, typically as a…

Computational Geometry · Computer Science 2026-03-27 Mathieu Carriere , Yuichi Ike , Théo Lacombe , Naoki Nishikawa

Persistent homology (PH) is a recently developed theory in the field of algebraic topology to study shapes of datasets. It is an effective data analysis tool that is robust to noise and has been widely applied. We demonstrate a general…

Signal Processing · Electrical Eng. & Systems 2020-05-05 Yu-Min Chung , Chuan-Shen Hu , Yu-Lun Lo , Hau-Tieng Wu

Persistent homology of the Rips filtration allows to track topological features of a point cloud over scales, and is a foundational tool of topological data analysis. Unfortunately, the Rips-filtration is exponentially sized, when…

Computational Geometry · Computer Science 2018-07-27 Bernhard Brehm , Hanne Hardering

In this work, following the Discrete de Rham (DDR) paradigm, we develop an arbitrary-order discrete divdiv complex on general polyhedral meshes. The construction rests 1) on discrete spaces that are spanned by vectors of polynomials whose…

Numerical Analysis · Mathematics 2024-09-13 Daniele A. Di Pietro , Marien-Lorenzo Hanot

Motivation: Array Comparative Genomic Hybridization (aCGH) is used to scan the entire genome for variations in DNA copy number. A central task in the analysis of aCGH data is the segmentation into groups of probes sharing the same DNA copy…

Quantitative Methods · Quantitative Biology 2008-04-29 Erez Ben-Yaacov , Yonina Eldar

Persistence diagram (PD) bundles, a generalization of vineyards, were introduced as a way to study the persistent homology of a set of filtrations parameterized by a topological space $B$. In this paper, we present an algorithm for…

Algebraic Topology · Mathematics 2023-09-21 Abigail Hickok

We initiate the study of persistent homology of random geometric simplicial complexes. Our main interest is in maximally persistent cycles of degree-$k$ in persistent homology, for a either the \cech or the Vietoris--Rips filtration built…

Probability · Mathematics 2016-05-17 Omer Bobrowski , Matthew Kahle , Primoz Skraba

Topological filters via sheaves generalize the classical linear translation-invariant filter theory by attaching the filter computation locally to a simplicial topological space. This paper develops topological filters for causal signal…

Signal Processing · Electrical Eng. & Systems 2021-10-07 Georg Essl

We develop a framework for computing the homology of weighted simplicial complexes with coefficients in a discrete valuation ring. A weighted simplicial complex, $(X,v)$, introduced by Dawson [Cah. Topol. G\'{e}om. Diff\'{e}r. Cat\'{e}g. 31…

Algebraic Topology · Mathematics 2022-05-10 Thomas J. X. Li , Christian M. Reidys

Persistent homology has been widely used to study the topology of point clouds in $\mathbb{R}^n$. Standard approaches are very sensitive to outliers, and their computational complexity depends badly on the number of data points. In this…

Algebraic Topology · Mathematics 2022-11-29 Pepijn Roos Hoefgeest , Lucas Slot

We solve the problem of minimizing the number of critical points among all functions on a surface within a prescribed distance {\delta} from a given input function. The result is achieved by establishing a connection between discrete Morse…

Computational Geometry · Computer Science 2015-05-07 Ulrich Bauer , Carsten Lange , Max Wardetzky

The rapid progress of Artificial Intelligence research came with the development of increasingly complex deep learning models, leading to growing challenges in terms of computational complexity, energy efficiency and interpretability. In…

Machine Learning · Computer Science 2023-06-28 Yuanrong Wang , Antonio Briola , Tomaso Aste

We study the homology of random \v{C}ech complexes generated by a homogeneous Poisson process. We focus on 'homological connectivity' - the stage where the random complex is dense enough, so that its homology "stabilizes" and becomes…

Probability · Mathematics 2019-06-14 Omer Bobrowski

We develop a version of discrete Morse theory for finite regular CW complexes equipped with an auxiliary stratification. The key construction is the halo of a cell, which contains all those faces in the boundary that enter closed…

Algebraic Topology · Mathematics 2026-01-27 Vidit Nanda , Francesca Tombari

In Persistent Homology and Topology, filtrations are usually given by introducing an ordered collection of sets or a continuous function from a topological space to $\R^n$. A natural question arises, whether these approaches are equivalent…

General Topology · Mathematics 2013-04-05 Barbara Di Fabio , Patrizio Frosini

Graph neural networks have become the default choice by practitioners for graph learning tasks such as graph classification and node classification. Nevertheless, popular graph neural network models still struggle to capture higher-order…

Machine Learning · Computer Science 2024-11-27 Davide Buffelli , Farzin Soleymani , Bastian Rieck