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Let $M$ denote a low-dimensional manifold embedded in Euclidean space and let ${X}= \{ x_1, \dots, x_n \}$ be a collection of points uniformly sampled from it. We study the relationship between the curvature of a random geometric graph…

Differential Geometry · Mathematics 2024-08-27 Nicolas Garcia Trillos , Melanie Weber

The existing research on robust Graph Neural Networks (GNNs) fails to acknowledge the significance of directed graphs in providing rich information about networks' inherent structure. This work presents the first investigation into the…

Machine Learning · Computer Science 2023-06-06 Zhichao Hou , Xitong Zhang , Wei Wang , Charu C. Aggarwal , Xiaorui Liu

Massive deployment of Graph Neural Networks (GNNs) in high-stake applications generates a strong demand for explanations that are robust to noise and align well with human intuition. Most existing methods generate explanations by…

Machine Learning · Computer Science 2022-07-14 Mohit Bajaj , Lingyang Chu , Zi Yu Xue , Jian Pei , Lanjun Wang , Peter Cho-Ho Lam , Yong Zhang

A graph $\Gamma$ is said to be stable if $\mathrm{Aut}(\Gamma\times K_2)\cong\mathrm{Aut}(\Gamma)\times \mathbb{Z}_{2}$ and unstable otherwise. If an unstable graph is connected, non-bipartite and any two of its distinct vertices have…

Combinatorics · Mathematics 2025-08-04 Junyang Zhang

We consider a $\varphi$-rigidity property for divergence-free vector fields in the Euclidean $n$-space, where $\varphi(t)$ is a non-negative convex function vanishing only at $t=0$. We show that this property is always satisfied in…

Analysis of PDEs · Mathematics 2022-03-01 Gian Paolo Leonardi , Giorgio Saracco

Contrastive learning (CL) has emerged as a powerful framework for learning representations of images and text in a self-supervised manner while enhancing model robustness against adversarial attacks. More recently, researchers have extended…

Machine Learning · Computer Science 2023-12-04 Filippo Guerranti , Zinuo Yi , Anna Starovoit , Rafiq Kamel , Simon Geisler , Stephan Günnemann

Liu, M\"unch, and Peyerimhoff introduced the notion of Bakry-\'Emery curvature for connection graphs as a means to derive Buser-type bounds on the eigenvalues of connection Laplacians. In this work, we present a reformulation of the…

Combinatorics · Mathematics 2026-04-08 Chunyang Hu , Shiping Liu

We introduce a novel definition of curvature for hypergraphs, a natural generalization of graphs, by introducing a multi-marginal optimal transport problem for a naturally defined random walk on the hypergraph. This curvature, termed…

Information Theory · Computer Science 2018-03-26 Shahab Asoodeh , Tingran Gao , James Evans

We revisit the concept of minimal rigidity as applied to soft repulsive, frictionless sphere packings in two-dimensions with the introduction of the jamming graph. Minimal rigidity is a purely combinatorial property encoded via Laman's…

Soft Condensed Matter · Physics 2015-06-16 Jorge H. Lopez , L. Cao , J. M. Schwarz

This paper deals with the question of prescribing the Gaussian curvature on a disk and the geodesic curvature of its boundary by means of a conformal deformation of the metric. We restrict ourselves to a symmetric setting in which the…

Differential Geometry · Mathematics 2025-01-27 Rafael López-Soriano , Francisco J. Reyes-Sánchez , David Ruiz

The purpose of this paper is to infer a global (collective) model of time-varying responses of a set of nodes as a dynamic graph, where the individual time series are respectively observed at each of the nodes. The motivation of this work…

Signal Processing · Electrical Eng. & Systems 2020-02-18 Bo Jiang , Ashkan Panahi , Hamid Krim , Yiyi Yu , Spencer L. Smith

The existence of adversarial examples has led to considerable uncertainty regarding the trust one can justifiably put in predictions produced by automated systems. This uncertainty has, in turn, lead to considerable research effort in…

Machine Learning · Computer Science 2019-08-02 Christina Göpfert , Jan Philip Göpfert , Barbara Hammer

This work analyzes Graph Neural Networks, a generalization of Fully-Connected Deep Neural Nets on Graph structured data, when their width, that is the number of nodes in each fullyconnected layer is increasing to infinity. Infinite Width…

Machine Learning · Computer Science 2023-11-21 Yunus Cobanoglu

In this paper, we study curvature dimension conditions on birth-death processes which correspond to linear graphs, i.e., weighted graphs supported on the infinite line or the half line. We give a combinatorial characterization of Bakry and…

Differential Geometry · Mathematics 2017-12-06 Bobo Hua , Florentin Münch

We study Forman--Ricci and effective resistance curvatures on the skeleta of convex polytopes. Our guiding questions are: how frequently do polytopal graphs exhibit everywhere positive curvature, and what structural constraints does…

Combinatorics · Mathematics 2025-10-15 Jesús A. De Loera , Jillian Eddy , Sawyer Jack Robertson , José Alejandro Samper

We investigate how to find generic and globally rigid realizations of graphs in $\mathbb{R}^d$ based on elementary geometric observations. Our arguments lead to new proofs of a combinatorial characterization of the global rigidity of graphs…

Combinatorics · Mathematics 2014-08-12 Shin-ichi Tanigawa

In hep-th/9910245, Witten and Yau consider the AdS/CFT correspondence in the context of a Riemannian Einstein manifold $M^{n+1}$ of negative Ricci curvature which admits a conformal compactification with conformal boundary $N^n$. They prove…

High Energy Physics - Theory · Physics 2007-05-23 Mingliang Cai , Gregory J. Galloway

Considerable recent attention has been given to the study of shape formation using modern responsive materials that can be preprogrammed to undergo spatially inhomogeneous local deformations. In particular, nematic liquid crystal polymer…

Soft Condensed Matter · Physics 2016-09-28 Cyrus Mostajeran , Taylor H. Ware , Timothy J. White

This work considers the robustness of uncertain consensus networks. The first set of results studies the stability properties of consensus networks with negative edge weights. We show that if either the negative weight edges form a cut in…

Optimization and Control · Mathematics 2015-03-03 Daniel Zelazo , Mathias Bürger

Computer or communication networks are so designed that they do not easily get disrupted under external attack and, moreover, these are easily reconstructible if they do get disrupted. These desirable properties of networks can be measured…

Combinatorics · Mathematics 2011-09-23 T. C. E. Cheng , Yinkui Li , Chuandong Xu , Shenggui Zhang
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