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Graphical models are a succinct way to represent the structure in probability distributions. This article analyzes the graphical model of nodal voltages in non-radial power distribution grids. Using algebraic and structural properties of…

Systems and Control · Computer Science 2020-02-28 Deepjyoti Deka , Saurav Talukdar , Michael Chertkov , Murti Salapaka

The paper addresses the problem of energy compaction of dense 4D light fields by designing geometry-aware local graph-based transforms. Local graphs are constructed on super-rays that can be seen as a grouping of spatially and…

Computer Vision and Pattern Recognition · Computer Science 2019-10-23 Mira Rizkallah , Xin Su , Thomas Maugey , Christine Guillemot

This is a tutorial and survey paper for nonlinear dimensionality and feature extraction methods which are based on the Laplacian of graph of data. We first introduce adjacency matrix, definition of Laplacian matrix, and the interpretation…

Machine Learning · Statistics 2022-08-09 Benyamin Ghojogh , Ali Ghodsi , Fakhri Karray , Mark Crowley

We present a graph-based numerical method for solving hyperbolic systems of conservation laws using discontinuous finite elements. This work fills important gaps in the theory as well as practice of graph-based schemes. In particular, four…

Numerical Analysis · Mathematics 2025-05-21 Martin Kronbichler , Matthias Maier , Ignacio Tomas

Diffusion models excel at creating visually impressive images but often struggle to generate images with a specified topology. The Betti number, which represents the number of structures in an image, is a fundamental measure in topology.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Saumya Gupta , Dimitris Samaras , Chao Chen

Diffusion generative models (DMs) have achieved promising results in image and graph generation. However, real-world graphs, such as social networks, molecular graphs, and traffic graphs, generally share non-Euclidean topologies and hidden…

Machine Learning · Computer Science 2024-01-04 Lingfeng Wen , Xuan Tang , Mingjie Ouyang , Xiangxiang Shen , Jian Yang , Daxin Zhu , Mingsong Chen , Xian Wei

We consider numerical solution of elliptic problems with heterogeneous diffusion coefficients containing thin highly conductive structures. Such problems arise e.g. in fractured porous media, reinforced materials, and electric circuits. The…

Numerical Analysis · Mathematics 2020-07-22 Fredrik Hellman , Axel Målqvist , Siyang Wang

The topology method is an algorithm for accurate estimation of instantaneous heartbeat intervals using millimeter-wave radar signals. In this model, feature points are extracted from the skin displacement waveforms generated by heartbeats…

Signal Processing · Electrical Eng. & Systems 2024-02-23 Yuji Tanaka , Kimitaka Sumi , Itsuki Iwata , Takuya Sakamoto

The chapter presents mathematical models intended for creating a topological drawing of a non-separable non-planar graph based on the methods of G. Ringel's vertex rotation theory. The induced system of cycles generates a topological…

Combinatorics · Mathematics 2025-07-23 Sergey Kurapov , Maxim Davidovsky

Faced with increasing penetration of distributed energy resources and fast development of distribution grid energy management, topology identification of distribution grid becomes an important and fundamental task. As the underlying grid…

Systems and Control · Electrical Eng. & Systems 2025-07-24 Yueyao Xu , Yize Chen

We determine the optimum topology of quasi-one dimensional nonlinear optical structures using generalized quantum graph models. Quantum graphs are relational graphs endowed with a metric and a multiparticle Hamiltonian acting on the edges,…

Quantum Physics · Physics 2015-06-19 Rick Lytel , Shoresh Shafei , Mark G. Kuzyk

In this paper, we design distributed multi-modal localization approaches for Connected and Automated vehicles. We utilize information diffusion on graphs formed by moving vehicles, based on Adapt-then-Combine strategies combined with the…

Signal Processing · Electrical Eng. & Systems 2024-11-07 Nikos Piperigkos , Aris S. Lalos , Kostas Berberidis

The Laplacian matrix and its pseudo-inverse for a strongly connected directed graph is fundamental in computing many properties of a directed graph. Examples include random-walk centrality and betweenness measures, average hitting and…

Numerical Analysis · Mathematics 2020-09-16 Daniel Boley

We investigate how the topology of attributed graphs influences the distribution of node attributes. This work offers a novel perspective by treating topology and attributes as structurally distinct but interacting components. We introduce…

Machine Learning · Computer Science 2026-02-03 Amirreza Shiralinasab Langari , Leila Yeganeh , Kim Khoa Nguyen

We develop a novel parallel decomposition strategy for unweighted, undirected graphs, based on growing disjoint connected clusters from batches of centers progressively selected from yet uncovered nodes. With respect to similar previous…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-02-09 Matteo Ceccarello , Andrea Pietracaprina , Geppino Pucci , Eli Upfal

Let $G$ be an infinite, edge- and vertex-weighted graph with certain reasonable restrictions. We construct the heat kernel of the associated Laplacian using an adaptation of the parametrix approach due to Minakshisundaram-Pleijel in the…

Analysis of PDEs · Mathematics 2024-09-10 Jay Jorgenson , Anders Karlsson , Lejla Smajlović

We consider the problem of designing spectral graph filters for the construction of dictionaries of atoms that can be used to efficiently represent signals residing on weighted graphs. While the filters used in previous spectral graph…

Functional Analysis · Mathematics 2013-11-06 David I Shuman , Christoph Wiesmeyr , Nicki Holighaus , Pierre Vandergheynst

We describe approximation algorithms in Linial's classic LOCAL model of distributed computing to find maximum-weight matchings in a hypergraph of rank $r$. Our main result is a deterministic algorithm to generate a matching which is an…

Data Structures and Algorithms · Computer Science 2023-10-13 David G. Harris

While deep convolutional architectures have achieved remarkable results in a gamut of supervised applications dealing with images and speech, recent works show that deep untrained non-convolutional architectures can also outperform…

Signal Processing · Electrical Eng. & Systems 2020-03-13 Samuel Rey , Antonio G. Marques , Santiago Segarra

We study an optimal control problem aimed at achieving a desired tradeoff between the network coherence and communication requirements in the distributed controller. Our objective is to add a certain number of edges to an undirected…

Optimization and Control · Mathematics 2018-11-26 Sepideh Hassan-Moghaddam , Mihailo R. Jovanović
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