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Titlebook: Maximum-Entropy Networks; Pattern Detection, N Tiziano Squartini,Diego Garlaschelli Book 2017 The Author(s) 2017 Complex Networks.Maximum-e

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發(fā)表于 2025-3-21 19:38:06 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Maximum-Entropy Networks
副標題Pattern Detection, N
編輯Tiziano Squartini,Diego Garlaschelli
視頻videohttp://file.papertrans.cn/628/627918/627918.mp4
概述A complete self-consistent introduction to a general methodology to study complex networks.Emphasizes the connections between pattern detection, network reconstruction and graph combinatorics.Includes
叢書名稱SpringerBriefs in Complexity
圖書封面Titlebook: Maximum-Entropy Networks; Pattern Detection, N Tiziano Squartini,Diego Garlaschelli Book 2017 The Author(s) 2017 Complex Networks.Maximum-e
描述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 refor
出版日期Book 2017
關鍵詞Complex Networks; Maximum-entropy Ensembles; Maximum likelihood estimation; Undirected networks; Directe
版次1
doihttps://doi.org/10.1007/978-3-319-69438-2
isbn_softcover978-3-319-69436-8
isbn_ebook978-3-319-69438-2Series ISSN 2191-5326 Series E-ISSN 2191-5334
issn_series 2191-5326
copyrightThe Author(s) 2017
The information of publication is updating

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SpringerBriefs in Complexityhttp://image.papertrans.cn/m/image/627918.jpg
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Maximum-Entropy Networks978-3-319-69438-2Series ISSN 2191-5326 Series E-ISSN 2191-5334
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Concluding Remarks,Now that we have reached the end of this book, we can look at its main contents in retrospect and try and make some overarching summary and remarks.
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https://doi.org/10.1007/978-3-319-69438-2Complex Networks; Maximum-entropy Ensembles; Maximum likelihood estimation; Undirected networks; Directe
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2191-5326 hapter 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 refor978-3-319-69436-8978-3-319-69438-2Series ISSN 2191-5326 Series E-ISSN 2191-5334
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