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Metric graphs are ubiquitous in science and engineering. For example, many data are drawn from hidden spaces that are graph-like, such as the cosmic web. A metric graph offers one of the simplest yet still meaningful ways to represent the…

Computational Geometry · Computer Science 2017-12-05 Tamal K. Dey , Dayu Shi , Yusu Wang

An ordered labeled tree is a tree in which the nodes are labeled and the left-to-right order among siblings is relevant. The edit distance between two ordered labeled trees is the minimum cost of changing one tree into the other through a…

Data Structures and Algorithms · Computer Science 2015-02-10 Shihyen Chen

We consider metrics which are preserved under a $p$-Wasserstein transport map, up to a possible contraction. In the case $p=1$ this corresponds to a metric which is uniformly curved in the sense of coarse Ricci curvature. We investigate the…

Probability · Mathematics 2017-12-08 Florian Völlering

The Weisfeiler-Lehman (WL) test is a widely used algorithm in graph machine learning, including graph kernels, graph metrics, and graph neural networks. However, it focuses only on the consistency of the graph, which means that it is unable…

Machine Learning · Computer Science 2023-05-02 Zhongxi Fang , Jianming Huang , Xun Su , Hiroyuki Kasai

We introduce a new notion of equivalence of discrete Morse functions on graphs called persistence equivalence. Two functions are considered persistence equivalent if and only if they induce the same persistence diagram. We compare this…

Algebraic Topology · Mathematics 2018-07-25 Yuqing Liu , Nicholas A. Scoville

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

This paper is concerned with the problem of defining and estimating statistics for distributions on spaces such as Riemannian manifolds and more general metric spaces. The challenge comes, in part, from the fact that statistics such as…

Statistics Theory · Mathematics 2025-05-29 Washington Mio , Tom Needham

As a fundamental problem of natural language processing, it is important to measure the distance between different documents. Among the existing methods, the Word Mover's Distance (WMD) has shown remarkable success in document semantic…

Machine Learning · Computer Science 2019-07-12 Zihao Wang , Datong Zhou , Yong Zhang , Hao Wu , Chenglong Bao

Given a collection of multidimensional pairs $\{(X_i,Y_i):1 \leq i\leq n\}$, we study the problem of projecting the associated suitably smoothed empirical measure onto the space of martingale couplings (i.e. distributions satisfying…

Probability · Mathematics 2025-10-20 Jose Blanchet , Johannes Wiesel , Erica Zhang , Zhenyuan Zhang

Reeb graphs are a fundamental structure for analyzing the topological and geometric properties of scalar fields. Comparing Reeb graphs is crucial for advancing research in this domain, yet existing metrics are often computationally…

Computational Geometry · Computer Science 2025-07-03 Erin W. Chambers , Guangyu Meng

The edit distance between two graphs on the same labeled vertex set is the size of the symmetric difference of the edge sets. The distance between a graph, $G$, and a hereditary property, ${\cal H}$, is the minimum of the distance between…

Combinatorics · Mathematics 2016-05-24 Ryan R. Martin

We develop a stability theory for minimal projective resolutions of $\mathbf{P}$-modules, where $\mathbf{P}$ is a finite metric poset. We use the G\"ulen-McCleary distance on $\mathbf{P}$-modules together with a new complex matching…

Representation Theory · Mathematics 2026-04-14 Hideto Asashiba , Amit K. Patel

The edit distance between two rooted ordered trees with $n$ nodes labeled from an alphabet~$\Sigma$ is the minimum cost of transforming one tree into the other by a sequence of elementary operations consisting of deleting and relabeling…

Data Structures and Algorithms · Computer Science 2017-03-28 Karl Bringmann , Paweł Gawrychowski , Shay Mozes , Oren Weimann

In this paper, we consider the problem of reconstructing trees from traces in the tree edit distance model. Previous work by Davies et al. (2019) analyzed special cases of reconstructing labeled trees. In this work, we significantly expand…

Computational Complexity · Computer Science 2022-01-14 Thomas Maranzatto

String Edit Distance is a more-than-classical problem whose behavior in the dynamic setting, where the strings are updated over time, is well studied. A single-character substitution, insertion, or deletion can be processed in time…

Data Structures and Algorithms · Computer Science 2025-11-18 Bingbing Hu , Jakob Nogler , Barna Saha

Gromov-Hausdorff (GH) distance is a natural way to measure the distortion between two metric spaces. However, there has been only limited algorithmic development to compute or approximate this distance. We focus on computing the…

Computational Geometry · Computer Science 2019-07-17 Elena Farahbakhsh Touli , Yusu Wang

An added edge to a graph is called an inset edge. Predicting k inset edges which minimize the average distance of a graph is known to be NP-Hard. When k = 1 the complexity of the problem is polynomial. In this paper, we further find the…

Data Structures and Algorithms · Computer Science 2020-08-14 M. H. Khalifeh , A. -H. Esfahanian

An added edge to a graph is called an inset edge. Predicting k inset edges which minimize the average distance of a graph is known to be NP-Hard. However, when k = 1 the complexity of the problem is polynomial. In this paper, some tools for…

Computational Complexity · Computer Science 2020-08-14 M. H. Khalifeh , A. -H. Esfahanian

Assume that an agent models a financial asset through a measure Q with the goal to price / hedge some derivative or optimize some expected utility. Even if the model Q is chosen in the most skilful and sophisticated way, she is left with…

Mathematical Finance · Quantitative Finance 2020-09-24 Julio Backhoff-Veraguas , Daniel Bartl , Mathias Beiglböck , Manu Eder

Given a probability measure with density, Fermat distances and density-driven metrics are conformal transformations of the Euclidean metric that shrink distances in high density areas and enlarge distances in low density areas. Although…

Statistics Theory · Mathematics 2026-01-22 Jérôme Taupin , Frédéric Chazal
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