Description: Maximum-Entropy Networks Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Pattern Detection, Network Reconstruction and Graph Combinatorics Author(s): Tiziano Squartini, Diego Garlaschelli Format: Paperback Publisher: Springer International Publishing AG, Switzerland Imprint: Springer International Publishing AG ISBN-13: 9783319694368, 978-3319694368 Synopsis 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 [url] 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.
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Book Title: Maximum-Entropy Networks
Item Height: 235 mm
Item Width: 155 mm
Series: Springerbriefs in Complexity
Author: Tiziano Squartini, Diego Garlaschelli
Publication Name: Maximum-Entropy Networks: Pattern Detection, Network Reconstruction and Graph Combinatorics
Format: Paperback
Language: English
Publisher: Springer International Publishing A&G
Subject: Computer Science, Mathematics, Physics
Publication Year: 2017
Type: Textbook
Item Weight: 2058 g
Number of Pages: 116 Pages
