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Author: B. Weisfeiler
Publisher: Springer
ISBN: 3540375392
Category : Mathematics
Languages : en
Pages : 251
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Book Description
Author: B. Weisfeiler
Publisher: Springer
ISBN: 3540375392
Category : Mathematics
Languages : en
Pages : 251
Get Book Here
Book Description
Author: William L. William L. Hamilton
Publisher: Springer Nature
ISBN: 3031015886
Category : Computers
Languages : en
Pages : 141
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Book Description
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.
Author: Gary Chartrand
Publisher: CRC Press
ISBN: 9781584883906
Category : Mathematics
Languages : en
Pages : 398
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Book Description
With a growing range of applications in fields from computer science to chemistry and communications networks, graph theory has enjoyed a rapid increase of interest and widespread recognition as an important area of mathematics. Through more than 20 years of publication, Graphs & Digraphs has remained a popular point of entry to the field, and through its various editions, has evolved with the field from a purely mathematical treatment to one that also addresses the mathematical needs of computer scientists. Carefully updated, streamlined, and enhanced with new features, Graphs & Digraphs, Fourth Edition reflects many of the developments in graph theory that have emerged in recent years. The authors have added discussions on topics of increasing interest, deleted outdated material, and judiciously augmented the Exercises sections to cover a range of problems that reach beyond the construction of proofs. New in the Fourth Edition: Expanded treatment of Ramsey theory Major revisions to the material on domination and distance New material on list colorings that includes interesting recent results A solutions manual covering many of the exercises available to instructors with qualifying course adoptions A comprehensive bibliography including an updated list of graph theory books Every edition of Graphs & Digraphs has been unique in its reflection the subject as one that is important, intriguing, and most of all beautiful. The fourth edition continues that tradition, offering a comprehensive, tightly integrated, and up-to-date introduction that imparts an appreciation as well as a solid understanding of the material.
Author: Jonathan L. Gross
Publisher: CRC Press
ISBN: 9780203490204
Category : Computers
Languages : en
Pages : 1200
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Book Description
The Handbook of Graph Theory is the most comprehensive single-source guide to graph theory ever published. Best-selling authors Jonathan Gross and Jay Yellen assembled an outstanding team of experts to contribute overviews of more than 50 of the most significant topics in graph theory-including those related to algorithmic and optimization approach
Author: Andries E. Brouwer
Publisher:
ISBN: 1316512037
Category : Language Arts & Disciplines
Languages : en
Pages : 481
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Book Description
This monograph on strongly regular graphs is an invaluable reference for anybody working in algebraic combinatorics.
Author: R.L. Graham
Publisher: Elsevier
ISBN: 008093384X
Category : Computers
Languages : en
Pages : 2404
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Book Description
Handbook of Combinatorics
Author: Ronald L. Graham
Publisher: Elsevier
ISBN: 9780444823465
Category : Business & Economics
Languages : en
Pages : 1124
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Book Description
Handbook of Combinatorics, Volume 1 focuses on basic methods, paradigms, results, issues, and trends across the broad spectrum of combinatorics. The selection first elaborates on the basic graph theory, connectivity and network flows, and matchings and extensions. Discussions focus on stable sets and claw free graphs, nonbipartite matching, multicommodity flows and disjoint paths, minimum cost circulations and flows, special proof techniques for paths and circuits, and Hamilton paths and circuits in digraphs. The manuscript then examines coloring, stable sets, and perfect graphs and embeddings and minors. The book takes a look at random graphs, hypergraphs, partially ordered sets, and matroids. Topics include geometric lattices, structural properties, linear extensions and correlation, dimension and posets of bounded degree, hypergraphs and set systems, stability, transversals, and matchings, and phase transition. The manuscript also reviews the combinatorial number theory, point lattices, convex polytopes and related complexes, and extremal problems in combinatorial geometry. The selection is a valuable reference for researchers interested in combinatorics.
Author: Dhananjay Kumar
Publisher: Springer Nature
ISBN: 9464632305
Category : Education
Languages : en
Pages : 1409
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Book Description
This is an open access book. The 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) was held on April 28–30, 2023 at the Xiamen, China. With the development of science and technology, information technology and information resources should be actively developed and fully applied in all fields of education and teaching, so as to promote the modernization of education and cultivate talents to meet the needs of society. From the technical point of view, the basic characteristics of educational informatization are digitalization, networking, intelligentization and multi-media. From the perspective of education, the basic characteristics of educational information are openness, sharing, interaction and cooperation. With the advantage of the network, it can provide students with a large amount of information and knowledge by combining different knowledge and information from various aspects in a high frequency. Therefore, we have intensified efforts to reform the traditional teaching methods and set up a new teaching concept, from the interaction between teachers and students in the past to the sharing between students. In short, it forms a sharing learning mode. For all students, strive to achieve students' learning independence, initiative and creativity. To sum up, we will provide a quick exchange platform between education and information technology, so that more scholars in related fields can share and exchange new ideas. The 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) was held on April 28-30, 2023 in Xiamen, China. IEIT 2023 is to bring together innovative academics and industrial experts in the field of Internet, Education and Information Technology to a common forum. The primary goal of the conference is to promote research and developmental activities in Internet, Education and Information Technology and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in international conference on Internet, Education and Information Technology and related areas.
Author: Lingfei Wu
Publisher: Springer Nature
ISBN: 9811660549
Category : Computers
Languages : en
Pages : 701
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Book Description
Deep Learning models are at the core of artificial intelligence research today. It is well known that deep learning techniques are disruptive for Euclidean data, such as images or sequence data, and not immediately applicable to graph-structured data such as text. This gap has driven a wave of research for deep learning on graphs, including graph representation learning, graph generation, and graph classification. The new neural network architectures on graph-structured data (graph neural networks, GNNs in short) have performed remarkably on these tasks, demonstrated by applications in social networks, bioinformatics, and medical informatics. Despite these successes, GNNs still face many challenges ranging from the foundational methodologies to the theoretical understandings of the power of the graph representation learning. This book provides a comprehensive introduction of GNNs. It first discusses the goals of graph representation learning and then reviews the history, current developments, and future directions of GNNs. The second part presents and reviews fundamental methods and theories concerning GNNs while the third part describes various frontiers that are built on the GNNs. The book concludes with an overview of recent developments in a number of applications using GNNs. This book is suitable for a wide audience including undergraduate and graduate students, postdoctoral researchers, professors and lecturers, as well as industrial and government practitioners who are new to this area or who already have some basic background but want to learn more about advanced and promising techniques and applications.
Author: Narsingh Deo
Publisher: PHI Learning Pvt. Ltd.
ISBN: 9788120301450
Category : Graph theory
Languages : en
Pages : 478
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Book Description
Because of its inherent simplicity, graph theory has a wide range of applications in engineering, and in physical sciences. It has of course uses in social sciences, in linguistics and in numerous other areas. In fact, a graph can be used to represent almost any physical situation involving discrete objects and the relationship among them. Now with the solutions to engineering and other problems becoming so complex leading to larger graphs, it is virtually difficult to analyze without the use of computers. This book is recommended in IIT Kharagpur, West Bengal for B.Tech Computer Science, NIT Arunachal Pradesh, NIT Nagaland, NIT Agartala, NIT Silchar, Gauhati University, Dibrugarh University, North Eastern Regional Institute of Management, Assam Engineering College, West Bengal Univerity of Technology (WBUT) for B.Tech, M.Tech Computer Science, University of Burdwan, West Bengal for B.Tech. Computer Science, Jadavpur University, West Bengal for M.Sc. Computer Science, Kalyani College of Engineering, West Bengal for B.Tech. Computer Science. Key Features: This book provides a rigorous yet informal treatment of graph theory with an emphasis on computational aspects of graph theory and graph-theoretic algorithms. Numerous applications to actual engineering problems are incorpo-rated with software design and optimization topics.
