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Analyzing large, multivariate graphs is an important problem in many domains, yet such graphs are challenging to visualize. In this paper, we introduce a novel, scalable, tree+table multivariate graph visualization technique, which makes…

Human-Computer Interaction · Computer Science 2018-08-03 Carolina Nobre , Marc Streit , Alexander Lex

Modeling multivariate time series has long been a subject that has attracted researchers from a diverse range of fields including economics, finance, and traffic. A basic assumption behind multivariate time series forecasting is that its…

Machine Learning · Computer Science 2020-05-26 Zonghan Wu , Shirui Pan , Guodong Long , Jing Jiang , Xiaojun Chang , Chengqi Zhang

Graph (or network) is a mathematical structure that has been widely used to model relational data. As real-world systems get more complex, multilayer (or multiple) networks are employed to represent diverse patterns of relationships among…

Methodology · Statistics 2024-06-10 Mingao Yuan , Qianqian Yao

Graphs are mathematical tools that can be used to represent complex real-world interconnected systems, such as financial markets and social networks. Hence, machine learning (ML) over graphs has attracted significant attention recently.…

Machine Learning · Computer Science 2023-10-24 O. Deniz Kose , Yanning Shen , Gonzalo Mateos

Modern energy systems in vehicles and built infrastructure are governed by high-dimensional dynamics spanning multiple physical domains (e.g., electrical, thermal, mechanical) and timescales. This tutorial paper presents a graph-based…

The family of image visibility graphs (IVGs) have been recently introduced as simple algorithms by which scalar fields can be mapped into graphs. Here we explore the usefulness of such operator in the scenario of image processing and image…

Data Analysis, Statistics and Probability · Physics 2019-11-19 Jacopo Iacovacci , Lucas Lacasa

In the last decade or so, we have witnessed deep learning reinvigorating the machine learning field. It has solved many problems in the domains of computer vision, speech recognition, natural language processing, and various other tasks…

Machine Learning · Computer Science 2021-09-09 Lilapati Waikhom , Ripon Patgiri

Graph processing has become an important part of various areas of computing, including machine learning, medical applications, social network analysis, computational sciences, and others. A growing amount of the associated graph processing…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-08-01 Maciej Besta , Marc Fischer , Vasiliki Kalavri , Michael Kapralov , Torsten Hoefler

This work presents some outcomes of a theoretical investigation of incompressible high-order networks defined by a generalized graph representation. We study some of their network topological properties and how these may be related to…

Information Theory · Computer Science 2019-05-15 Felipe S. Abrahão , Klaus Wehmuth , Artur Ziviani

Multimodal attributed graphs (MAGs) combine multimodal node attributes with structured relations. However, existing methods usually perform shared message passing on a single graph and implicitly assume that the same neighbors are equally…

Machine Learning · Computer Science 2026-04-15 Yilong Zuo , Xunkai Li , Zhihan Zhang , Ronghua Li , Guoren Wang

High-dimensional multiplex graphs are characterized by their high number of complementary and divergent dimensions. The existence of multiple hierarchical latent relations between the graph dimensions poses significant challenges to…

Machine Learning · Computer Science 2025-01-30 Kamel Abdous , Nairouz Mrabah , Mohamed Bouguessa

This article discusses how concepts and methods of complex networks can be applied to real-time imaging and computer vision. After a brief introduction of complex networks basic concepts, their use as means to represent and characterize…

Computer Vision and Pattern Recognition · Computer Science 2007-05-23 Luciano da Fontoura Costa

This paper proposes an adaptive graph-based approach for multi-label image classification. Graph-based methods have been largely exploited in the field of multi-label classification, given their ability to model label correlations.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Indel Pal Singh , Enjie Ghorbel , Oyebade Oyedotun , Djamila Aouada

Efficient processing of large-scale graphs in distributed environments has been an increasingly popular topic of research in recent years. Inter-connected data that can be modeled as graphs arise in application domains such as machine…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-01-25 Vasiliki Kalavri , Vladimir Vlassov , Seif Haridi

Graph-based modeling plays a fundamental role in many areas of computer science. In this paper, we introduce systems of graph formulas with variables for specifying graph properties; this notion generalizes the graph formulas introduced in…

Formal Languages and Automata Theory · Computer Science 2026-01-23 Frank Drewes , Berthold Hoffmann , Mark Minas

Graphs have a superior ability to represent relational data, like chemical compounds, proteins, and social networks. Hence, graph-level learning, which takes a set of graphs as input, has been applied to many tasks including comparison,…

Machine Learning · Computer Science 2023-05-26 Zhenyu Yang , Ge Zhang , Jia Wu , Jian Yang , Quan Z. Sheng , Shan Xue , Chuan Zhou , Charu Aggarwal , Hao Peng , Wenbin Hu , Edwin Hancock , Pietro Liò

The success of scene graphs for visual scene understanding has brought attention to the benefits of abstracting a visual input (e.g., image) into a structured representation, where entities (people and objects) are nodes connected by edges…

Computer Vision and Pattern Recognition · Computer Science 2022-10-28 Mohamed Ashraf Abdelsalam , Zhan Shi , Federico Fancellu , Kalliopi Basioti , Dhaivat J. Bhatt , Vladimir Pavlovic , Afsaneh Fazly

Graphs are ubiquitous in nature and can therefore serve as models for many practical but also theoretical problems. For this purpose, they can be defined as many different types which suitably reflect the individual contexts of the…

Machine Learning · Computer Science 2023-04-27 Josephine M. Thomas , Alice Moallemy-Oureh , Silvia Beddar-Wiesing , Clara Holzhüter

Considered in this paper is the method of describingc of telecommunications systems providing VoD service using multi-layer graph. The paper describes the relations between the structural elements at each hierarchical level of the…

Networking and Internet Architecture · Computer Science 2012-03-07 Dmitry Ageyev , Artem Ignatenko

The increasing interest in complex networks research has been a consequence of several intrinsic features of this area, such as the generality of the approach to represent and model virtually any discrete system, and the incorporation of…

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