Mathematical Foundations And Applications Of Graph Entropy
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Mathematical Foundations and Applications of Graph Entropy
Author | : Matthias Dehmer,Frank Emmert-Streib,Zengqiang Chen,Xueliang Li,Yongtang Shi |
Publsiher | : John Wiley & Sons |
Total Pages | : 298 |
Release | : 2017-09-12 |
Genre | : Medical |
ISBN | : 9783527339099 |
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This latest addition to the successful Network Biology series presents current methods for determining the entropy of networks, making it the first to cover the recently established Quantitative Graph Theory. An excellent international team of editors and contributors provides an up-to-date outlook for the field, covering a broad range of graph entropy-related concepts and methods. The topics range from analyzing mathematical properties of methods right up to applying them in real-life areas. Filling a gap in the contemporary literature this is an invaluable reference for a number of disciplines, including mathematicians, computer scientists, computational biologists, and structural chemists.
Quantitative Graph Theory
Author | : Matthias Dehmer,Frank Emmert-Streib |
Publsiher | : CRC Press |
Total Pages | : 530 |
Release | : 2014-10-27 |
Genre | : Computers |
ISBN | : 9781466584518 |
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The first book devoted exclusively to quantitative graph theory, Quantitative Graph Theory: Mathematical Foundations and Applications presents and demonstrates existing and novel methods for analyzing graphs quantitatively. Incorporating interdisciplinary knowledge from graph theory, information theory, measurement theory, and statistical techniques, this book covers a wide range of quantitative-graph theoretical concepts and methods, including those pertaining to real and random graphs such as: Comparative approaches (graph similarity or distance) Graph measures to characterize graphs quantitatively Applications of graph measures in social network analysis and other disciplines Metrical properties of graphs and measures Mathematical properties of quantitative methods or measures in graph theory Network complexity measures and other topological indices Quantitative approaches to graphs using machine learning (e.g., clustering) Graph measures and statistics Information-theoretic methods to analyze graphs quantitatively (e.g., entropy) Through its broad coverage, Quantitative Graph Theory: Mathematical Foundations and Applications fills a gap in the contemporary literature of discrete and applied mathematics, computer science, systems biology, and related disciplines. It is intended for researchers as well as graduate and advanced undergraduate students in the fields of mathematics, computer science, mathematical chemistry, cheminformatics, physics, bioinformatics, and systems biology.
Modern and Interdisciplinary Problems in Network Science
Author | : Zengqiang Chen,Matthias Dehmer,Frank Emmert-Streib,Yongtang Shi |
Publsiher | : CRC Press |
Total Pages | : 276 |
Release | : 2018-09-05 |
Genre | : Mathematics |
ISBN | : 9781351237284 |
Download Modern and Interdisciplinary Problems in Network Science Book in PDF, Epub and Kindle
Modern and Interdisciplinary Problems in Network Science: A Translational Research Perspective covers a broad range of concepts and methods, with a strong emphasis on interdisciplinarity. The topics range from analyzing mathematical properties of network-based methods to applying them to application areas. By covering this broad range of topics, the book aims to fill a gap in the contemporary literature in disciplines such as physics, applied mathematics and information sciences.
Intelligent Computing
Author | : Kohei Arai,Supriya Kapoor,Rahul Bhatia |
Publsiher | : Springer Nature |
Total Pages | : 721 |
Release | : 2020-07-03 |
Genre | : Technology & Engineering |
ISBN | : 9783030522438 |
Download Intelligent Computing Book in PDF, Epub and Kindle
This book focuses on the core areas of computing and their applications in the real world. Presenting papers from the Computing Conference 2020 covers a diverse range of research areas, describing various detailed techniques that have been developed and implemented. The Computing Conference 2020, which provided a venue for academic and industry practitioners to share new ideas and development experiences, attracted a total of 514 submissions from pioneering academic researchers, scientists, industrial engineers and students from around the globe. Following a double-blind, peer-review process, 160 papers (including 15 poster papers) were selected to be included in these proceedings. Featuring state-of-the-art intelligent methods and techniques for solving real-world problems, the book is a valuable resource and will inspire further research and technological improvements in this important area.
ICICKM 2018 15th International Conference on Intellectual Capital Knowledge Management Organisational Learning
Author | : Prof. Shaun Pather |
Publsiher | : Academic Conferences and publishing limited |
Total Pages | : 135 |
Release | : 2018-11-29 |
Genre | : Business & Economics |
ISBN | : 9781912764105 |
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Mathematical Theory of Entropy
Author | : Nathaniel F. G. Martin,James W. England |
Publsiher | : Cambridge University Press |
Total Pages | : 292 |
Release | : 2011-06-02 |
Genre | : Computers |
ISBN | : 0521177383 |
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This excellent 1981 treatment of the mathematical theory of entropy gives an accessible exposition its application to other fields.
Maximum Entropy Networks
Author | : Tiziano Squartini,Diego Garlaschelli |
Publsiher | : Springer |
Total Pages | : 116 |
Release | : 2017-11-22 |
Genre | : Science |
ISBN | : 9783319694382 |
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This book is an introduction to maximum-entropy models of random graphs with given topological properties and their applications. Its original contribution is the reformulation of many seemingly different problems in the study of both real networks and graph theory within the unified framework of maximum entropy. Particular emphasis is put on the detection of structural patterns in real networks, on the reconstruction of the properties of networks from partial information, and on the enumeration and sampling of graphs with given properties. After a first introductory chapter explaining the motivation, focus, aim and message of the book, chapter 2 introduces the formal construction of maximum-entropy ensembles of graphs with local topological constraints. Chapter 3 focuses on the problem of pattern detection in real networks and provides a powerful way to disentangle nontrivial higher-order structural features from those that can be traced back to simpler local constraints. Chapter 4 focuses on the problem of network reconstruction and introduces various advanced techniques to reliably infer the topology of a network from partial local information. Chapter 5 is devoted to the reformulation of certain “hard” combinatorial operations, such as the enumeration and unbiased sampling of graphs with given constraints, within a “softened” maximum-entropy framework. A final chapter offers various overarching remarks and take-home messages.By requiring no prior knowledge of network theory, the book targets a broad audience ranging from PhD students approaching these topics for the first time to senior researchers interested in the application of advanced network techniques to their field.
Mathematical Foundations of Information Theory
Author | : Aleksandr I?Akovlevich Khinchin |
Publsiher | : Courier Corporation |
Total Pages | : 150 |
Release | : 1957-01-01 |
Genre | : Mathematics |
ISBN | : 0486604349 |
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First comprehensive introduction to information theory explores the work of Shannon, McMillan, Feinstein, and Khinchin. Topics include the entropy concept in probability theory, fundamental theorems, and other subjects. 1957 edition.