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An Introduction to Grids, Graphs, and Networks

An Introduction to Grids, Graphs, and Networks
Author: C. Pozrikidis
Publisher: Oxford University Press
Total Pages: 299
Release: 2014-02-17
Genre: Mathematics
ISBN: 0199996733

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An Introduction to Grids, Graphs, and Networks aims to provide a concise introduction to graphs and networks at a level that is accessible to scientists, engineers, and students. In a practical approach, the book presents only the necessary theoretical concepts from mathematics and considers a variety of physical and conceptual configurations as prototypes or examples. The subject is timely, as the performance of networks is recognized as an important topic in the study of complex systems with applications in energy, material, and information grid transport (epitomized by the internet). The book is written from the practical perspective of an engineer with some background in numerical computation and applied mathematics, and the text is accompanied by numerous schematic illustrations throughout. In the book, Constantine Pozrikidis provides an original synthesis of concepts and terms from three distinct fields-mathematics, physics, and engineering-and a formal application of powerful conceptual apparatuses, like lattice Green's function, to areas where they have rarely been used. It is novel in that its grids, graphs, and networks are connected using concepts from partial differential equations. This original material has profound implications in the study of networks, and will serve as a resource to readers ranging from undergraduates to experienced scientists.


Finite Graphs and Networks

Finite Graphs and Networks
Author: Robert G. Busacker
Publisher:
Total Pages: 320
Release: 1965
Genre: Mathematics
ISBN:

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Graphs and Networks

Graphs and Networks
Author: W. L. Price
Publisher:
Total Pages: 124
Release: 1971
Genre: Mathematics
ISBN:

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Graph Representation Learning

Graph Representation Learning
Author: William L. William L. Hamilton
Publisher: Springer Nature
Total Pages: 141
Release: 2022-06-01
Genre: Computers
ISBN: 3031015886

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Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.


Handbook of Graphs and Networks

Handbook of Graphs and Networks
Author: Stefan Bornholdt
Publisher: John Wiley & Sons
Total Pages: 417
Release: 2006-03-06
Genre: Science
ISBN: 3527606335

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Complex interacting networks are observed in systems from such diverse areas as physics, biology, economics, ecology, and computer science. For example, economic or social interactions often organize themselves in complex network structures. Similar phenomena are observed in traffic flow and in communication networks as the internet. In current problems of the Biosciences, prominent examples are protein networks in the living cell, as well as molecular networks in the genome. On larger scales one finds networks of cells as in neural networks, up to the scale of organisms in ecological food webs. This book defines the field of complex interacting networks in its infancy and presents the dynamics of networks and their structure as a key concept across disciplines. The contributions present common underlying principles of network dynamics and their theoretical description and are of interest to specialists as well as to the non-specialized reader looking for an introduction to this new exciting field. Theoretical concepts include modeling networks as dynamical systems with numerical methods and new graph theoretical methods, but also focus on networks that change their topology as in morphogenesis and self-organization. The authors offer concepts to model network structures and dynamics, focussing on approaches applicable across disciplines.


Graph Theory and Complex Networks

Graph Theory and Complex Networks
Author: Maarten van Steen
Publisher: Maarten Van Steen
Total Pages: 285
Release: 2010
Genre: Graph theory
ISBN: 9789081540612

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This book aims to explain the basics of graph theory that are needed at an introductory level for students in computer or information sciences. To motivate students and to show that even these basic notions can be extremely useful, the book also aims to provide an introduction to the modern field of network science. Mathematics is often unnecessarily difficult for students, at times even intimidating. For this reason, explicit attention is paid in the first chapters to mathematical notations and proof techniques, emphasizing that the notations form the biggest obstacle, not the mathematical concepts themselves. This approach allows to gradually prepare students for using tools that are necessary to put graph theory to work: complex networks. In the second part of the book the student learns about random networks, small worlds, the structure of the Internet and the Web, peer-to-peer systems, and social networks. Again, everything is discussed at an elementary level, but such that in the end students indeed have the feeling that they: 1.Have learned how to read and understand the basic mathematics related to graph theory. 2.Understand how basic graph theory can be applied to optimization problems such as routing in communication networks. 3.Know a bit more about this sometimes mystical field of small worlds and random networks. There is an accompanying web site www.distributed-systems.net/gtcn from where supplementary material can be obtained, including exercises, Mathematica notebooks, data for analyzing graphs, and generators for various complex networks.


Graphs and Networks

Graphs and Networks
Author: Bernard Carré
Publisher: Oxford University Press, USA
Total Pages: 300
Release: 1979
Genre: Mathematics
ISBN:

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Graph Theoretic Methods in Multiagent Networks

Graph Theoretic Methods in Multiagent Networks
Author: Mehran Mesbahi
Publisher: Princeton University Press
Total Pages: 424
Release: 2010-07-01
Genre: Mathematics
ISBN: 1400835356

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This accessible book provides an introduction to the analysis and design of dynamic multiagent networks. Such networks are of great interest in a wide range of areas in science and engineering, including: mobile sensor networks, distributed robotics such as formation flying and swarming, quantum networks, networked economics, biological synchronization, and social networks. Focusing on graph theoretic methods for the analysis and synthesis of dynamic multiagent networks, the book presents a powerful new formalism and set of tools for networked systems. The book's three sections look at foundations, multiagent networks, and networks as systems. The authors give an overview of important ideas from graph theory, followed by a detailed account of the agreement protocol and its various extensions, including the behavior of the protocol over undirected, directed, switching, and random networks. They cover topics such as formation control, coverage, distributed estimation, social networks, and games over networks. And they explore intriguing aspects of viewing networks as systems, by making these networks amenable to control-theoretic analysis and automatic synthesis, by monitoring their dynamic evolution, and by examining higher-order interaction models in terms of simplicial complexes and their applications. The book will interest graduate students working in systems and control, as well as in computer science and robotics. It will be a standard reference for researchers seeking a self-contained account of system-theoretic aspects of multiagent networks and their wide-ranging applications. This book has been adopted as a textbook at the following universities: ? University of Stuttgart, Germany Royal Institute of Technology, Sweden Johannes Kepler University, Austria Georgia Tech, USA University of Washington, USA Ohio University, USA


GRAPHS AND NETWORKS

GRAPHS AND NETWORKS
Author: Wyn L. Price
Publisher:
Total Pages: 108
Release: 1971
Genre:
ISBN:

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Introduction to Graph Signal Processing

Introduction to Graph Signal Processing
Author: Antonio Ortega
Publisher: Cambridge University Press
Total Pages:
Release: 2022-06-09
Genre: Technology & Engineering
ISBN: 1108640176

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An intuitive and accessible text explaining the fundamentals and applications of graph signal processing. Requiring only an elementary understanding of linear algebra, it covers both basic and advanced topics, including node domain processing, graph signal frequency, sampling, and graph signal representations, as well as how to choose a graph. Understand the basic insights behind key concepts and learn how graphs can be associated to a range of specific applications across physical, biological and social networks, distributed sensor networks, image and video processing, and machine learning. With numerous exercises and Matlab examples to help put knowledge into practice, and a solutions manual available online for instructors, this unique text is essential reading for graduate and senior undergraduate students taking courses on graph signal processing, signal processing, information processing, and data analysis, as well as researchers and industry professionals.