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Graph-structured data such as social networks, functional brain networks, gene regulatory networks, communications networks have brought the interest in generalizing deep learning techniques to graph domains. In this paper, we are…

Machine Learning · Computer Science 2018-04-25 Xavier Bresson , Thomas Laurent

Edge reconstruction modifies the electronic properties of finite graphene samples. We formulate a low-energy theory of the reconstructed zigzag edge by deriving the modified boundary condition to the Dirac equation. If the unit cell size of…

Mesoscale and Nanoscale Physics · Physics 2013-07-09 J. A. M. van Ostaay , A. R. Akhmerov , C. W. J. Beenakker , M. Wimmer

We consider an ideal gas of infinitely rigid rods near a perfectly repulsive wall, and show that the interfacial tension of a surface with rods on one side is lower when the surface bends towards the rods. Surprisingly we find that rods on…

Soft Condensed Matter · Physics 2015-06-25 K. Yaman , M. Jeng , P. Pincus , C. Jeppesen , C. M. Marques

Tanigawa (2016) showed that vertex-redundant rigidity of a graph implies its global rigidity in arbitrary dimension. We extend this result to periodic graphs under fixed lattice representations. A periodic graph is vertex-redundantly rigid…

Metric Geometry · Mathematics 2018-04-24 Viktoria E. Kaszanitzky , Csaba Kiraly , Bernd Schulze

The goal of graph inference is to design algorithms for learning properties of a hidden graph using queries to an oracle that returns information about the graph. Graph reconstruction, verification, and property testing are all types of…

Data Structures and Algorithms · Computer Science 2025-02-26 Huck Bennett , Mitchell Black , Amir Nayyeri , Evelyn Warton

The edit distance between two graphs is a widely used measure of similarity that evaluates the smallest number of vertex and edge deletions/insertions required to transform one graph to another. It is NP-hard to compute in general, and a…

Data Structures and Algorithms · Computer Science 2019-04-22 Utkan Onur Candogan , Venkat Chandrasekaran

We study resistance sparsification of graphs, in which the goal is to find a sparse subgraph (with reweighted edges) that approximately preserves the effective resistances between every pair of nodes. We show that every dense regular…

Data Structures and Algorithms · Computer Science 2015-06-26 Michael Dinitz , Robert Krauthgamer , Tal Wagner

We develop a new approach and employ it to establish the global existence and nonlinear structural stability of attached weak transonic shocks in steady potential flow past three-dimensional wedges; in particular, the restriction that the…

Analysis of PDEs · Mathematics 2021-08-10 Gui-Qiang G. Chen , Jun Chen , Wei Xiang

This paper investigates a diffusion process in a narrow tubular domain with reflecting boundary conditions, where the geometry serves as a singular perturbation of an underlying graph in $\mathbb{R}^2$ or $\mathbb{R}^3$. The construction…

Probability · Mathematics 2025-09-04 Wen-Tai Hsu

In many complex networks the vertices are ordered in time, and edges represent causal connections. We propose methods of analysing such directed acyclic graphs taking into account the constraints of causality and highlighting the causal…

Physics and Society · Physics 2015-07-07 James R. Clough , Jamie Gollings , Tamar V. Loach , Tim S. Evans

We propose a new method for embedding graphs while preserving directed edge information. Learning such continuous-space vector representations (or embeddings) of nodes in a graph is an important first step for using network information…

Machine Learning · Computer Science 2017-09-15 Sami Abu-El-Haija , Bryan Perozzi , Rami Al-Rfou

Assessing and improving the robustness of a graph $G$ are critical steps in network design and analysis. To this end, we consider the optimisation problem of removing $k$ edges from $G$ such that the resulting graph has minimal robustness,…

Social and Information Networks · Computer Science 2024-07-17 Lukas Berner , Henning Meyerhenke

Deep Graph Networks (DGNs) currently dominate the research landscape of learning from graphs, due to their efficiency and ability to implement an adaptive message-passing scheme between the nodes. However, DGNs are typically limited in…

Machine Learning · Computer Science 2023-02-09 Alessio Gravina , Davide Bacciu , Claudio Gallicchio

Compression and sparsification algorithms are frequently applied in a preprocessing step before analyzing or optimizing large networks/graphs. In this paper we propose and study a new framework contracting edges of a graph (merging vertices…

Data Structures and Algorithms · Computer Science 2019-02-14 Aaron Bernstein , Karl Däubel , Yann Disser , Max Klimm , Torsten Mütze , Frieder Smolny

We perform the first adversarial robustness study into Graph Neural Networks (GNNs) that are provably more powerful than traditional Message Passing Neural Networks (MPNNs). In particular, we use adversarial robustness as a tool to uncover…

Machine Learning · Computer Science 2024-07-04 Francesco Campi , Lukas Gosch , Tom Wollschläger , Yan Scholten , Stephan Günnemann

We consider a new problem of designing a network with small $s$-$t$ effective resistance. In this problem, we are given an undirected graph $G=(V,E)$, two designated vertices $s,t \in V$, and a budget $k$. The goal is to choose a subgraph…

Data Structures and Algorithms · Computer Science 2019-04-09 Pak Hay Chan , Lap Chi Lau , Aaron Schild , Sam Chiu-wai Wong , Hong Zhou

This paper considers a kind of generalized measure $\lambda_s^{(h)}$ of fault tolerance in a hypercube-like graph $G_n$ which contain several well-known interconnection networks such as hypercubes, varietal hypercubes, twisted cubes,…

Combinatorics · Mathematics 2012-12-21 Xiang-Jun Li , Jun-Ming Xu

The goal is to show that an edge-reinforced random walk on a graph of bounded degree, with reinforcement weight function $W$ taken from a general class of reciprocally summable reinforcement weight functions, traverses a random attracting…

Probability · Mathematics 2009-09-29 Vlada Limic , Pierre Tarrès

In weighted graphs the shortest path between two nodes is often reached through an indirect path, out of all possible connections, leading to structural redundancies which play key roles in the dynamics and evolution of complex networks. We…

Social and Information Networks · Computer Science 2023-06-14 Felipe Xavier Costa , Rion Brattig Correia , Luis M. Rocha

We derive a dimension-reduction limit for a three-dimensional rod with material voids by means of $\Gamma$-convergence. Hereby, we generalize the results of the purely elastic setting [57] to a framework of free discontinuity problems. The…

Analysis of PDEs · Mathematics 2023-11-30 Manuel Friedrich , Leonard Kreutz , Konstantinos Zemas
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