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Comparing two geometric graphs embedded in space is important in the field of transportation network analysis. Given street maps of the same city collected from different sources, researchers often need to know how and where they differ.…

Computational Geometry · Computer Science 2015-02-17 Mahmuda Ahmed , Brittany Terese Fasy , Kyle S. Hickmann , Carola Wenk

It is by now a well known fact in the graph learning community that the presence of bottlenecks severely limits the ability of graph neural networks to propagate information over long distances. What so far has not been appreciated is that,…

Machine Learning · Computer Science 2023-10-31 Christian Koke , Abhishek Saroha , Yuesong Shen , Marvin Eisenberger , Daniel Cremers

Zigzag persistent homology is a powerful generalisation of persistent homology that allows one not only to compute persistence diagrams with less noise and using less memory, but also to use persistence in new fields of application.…

Computational Geometry · Computer Science 2016-08-23 Clément Maria , Steve Oudot

Heterogeneous datasets emerge in various machine learning and optimization applications that feature different input sources, types or formats. Most models or methods do not natively tackle heterogeneity. Hence, such datasets are often…

Machine Learning · Statistics 2025-08-25 Edward Hallé-Hannan , Charles Audet , Youssef Diouane , Sébastien Le Digabel , Paul Saves

We investigate how effectively finite metric spaces can be distinguished by distance-based invariants. As model spaces, we consider regular polygons, cycle graphs, and their generalization, circular metric spaces, and as invariants we…

Metric Geometry · Mathematics 2026-04-07 Hiroki Kodama , Jun O'Hara

The homotopy interleaving distance, a distance between persistent spaces, was introduced by Blumberg and Lesnick and shown to be universal, in the sense that it is the largest homotopy-invariant distance for which sublevel-set filtrations…

Algebraic Topology · Mathematics 2023-05-17 Edoardo Lanari , Luis Scoccola

Multivariate time series are ubiquitous objects in signal processing. Measuring a distance or similarity between two such objects is of prime interest in a variety of applications, including machine learning, but can be very difficult as…

Machine Learning · Statistics 2022-11-02 Titouan Vayer , Romain Tavenard , Laetitia Chapel , Nicolas Courty , Rémi Flamary , Yann Soullard

This paper establishes a general topological condition under which the semilocal stability of a set-valued mapping can be exactly determined by its local stability properties. Specifically, we investigate the relationship between the…

Optimization and Control · Mathematics 2026-03-12 J. Camacho

We consider parallel simulations for asynchronous systems employing L processing elements that are arranged on a ring. Processors communicate only among the nearest neighbors and advance their local simulated time only if it is guaranteed…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 A. Kolakowska , M. A. Novotny , G. Korniss

A 2-dimensional direction-length framework is a collection of points in the plane which are linked by pairwise constraints that fix the direction or length of the line segments joining certain pairs of points. We represent it as a pair…

Combinatorics · Mathematics 2016-07-05 Katie Clinch , Bill Jackson , Peter Keevash

We prove that the space of persistence diagrams on $n$ points (with the bottleneck or a Wasserstein distance) coarsely embeds into Hilbert space by showing it is of asymptotic dimension $2n$. Such an embedding enables utilisation of Hilbert…

Metric Geometry · Mathematics 2021-10-22 Atish Mitra , Žiga Virk

We use weights on objects in an abelian category to define what we call a path metric. We introduce three special classes of weight: those compatible with short exact sequences; those induced by their path metric; and those which bound…

Rings and Algebras · Mathematics 2025-02-19 Peter Bubenik , Jonathan Scott , Donald Stanley

A graph is edge-distance-regular when it is distance-regular around each of its edges and it has the same intersection numbers for any edge taken as a root. In this paper we give some (combinatorial and algebraic) proofs of the fact that…

Combinatorics · Mathematics 2012-10-23 M. Cámara , C. Dalfó , C. Delorme , M. A. Fiol , H. Suzuki

We use persistence modules and their corresponding barcodes to quantitatively distinguish between different fiberwise star-shaped domains in the cotangent bundle of a fixed manifold. The distance between two fiberwise star-shaped domains is…

Symplectic Geometry · Mathematics 2019-12-16 Vukašin Stojisavljević , Jun Zhang

We show that large subsets of vector spaces over finite fields determine certain point configurations with prescribed distance structure. More specifically, we consider the complete graph with vertices as the points of $A \subseteq…

Combinatorics · Mathematics 2018-02-20 Alex Iosevich , Hans Parshall

Distance measures play an important role in shape classification and data analysis problems. Topological distances based on Reeb graphs and persistence diagrams have been employed to obtain effective algorithms in shape matching and scalar…

Machine Learning · Computer Science 2023-03-07 Yashwanth Ramamurthi , Amit Chattopadhyay

To quantify the fundamental evolution of time-varying networks, and detect abnormal behavior, one needs a notion of temporal difference that captures significant organizational changes between two successive instants. In this work, we…

Social and Information Networks · Computer Science 2017-08-17 Nathan D Monnig , Francois G Meyer

For a finite point set $E\subset \mathbb{R}^d$ and a connected graph $G$ on $k+1$ vertices, we define a $G$-framework to be a collection of $k + 1$ points in E such that the distance between a pair of points is specified if the…

Combinatorics · Mathematics 2018-05-22 A. Iosevich , J. Passant

Data consisting of a graph with a function mapping into $\mathbb{R}^d$ arise in many data applications, encompassing structures such as Reeb graphs, geometric graphs, and knot embeddings. As such, the ability to compare and cluster such…

Computational Geometry · Computer Science 2025-07-17 Erin W. Chambers , Elizabeth Munch , Sarah Percival , Bei Wang

Many applications in pattern recognition represent patterns as a geometric graph. The geometric graph distance (GGD) has recently been studied as a meaningful measure of similarity between two geometric graphs. Since computing the GGD is…

Computational Geometry · Computer Science 2023-06-12 Sushovan Majhi
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