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Complex networks datasets often come with the problem of missing information: interactions data that have not been measured or discovered, may be affected by errors, or are simply hidden because of privacy issues. This Element provides an overview of the ideas, methods and techniques to deal with this problem and that together define the field of network reconstruction. Given the extent of the subject, the authors focus on the inference methods rooted in statistical physics and information theory. The discussion is organized according to the different scales of the reconstruction task, that is, whether the goal is to reconstruct the macroscopic structure of the network, to infer its mesoscale properties, or to predict the individual microscopic connections.
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Reconstructing Networks (Elements in the Structure and Dynamics of Complex Networks)
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Reconstructing Networks (Elements in Structure and Dynamics of Complex Networks)
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Reconstructing Networks
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Reconstructing Networks
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Reconstructing Networks (Paperback)
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ISBN 10: 110872681X
ISBN 13: 9781108726818
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Paperback. Condition: new. Paperback. Complex networks datasets often come with the problem of missing information: interactions data that have not been measured or discovered, may be affected by errors, or are simply hidden because of privacy issues. This Element provides an overview of the ideas, methods and techniques to deal with this problem and that together define the field of network reconstruction. Given the extent of the subject, the authors focus on the inference methods rooted in statistical physics and information theory. The discussion is organized according to the different scales of the reconstruction task, that is, whether the goal is to reconstruct the macroscopic structure of the network, to infer its mesoscale properties, or to predict the individual microscopic connections. This Element provides an overview of the ideas, methods and techniques to deal with the problem of missing information in complex networks datasets. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781108726818
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Reconstructing Networks (Elements in the Structure and Dynamics of Complex Networks)
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Cambridge University Press, 2021
ISBN 10: 110872681X
ISBN 13: 9781108726818
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Reconstructing Networks (Elements in the Structure and Dynamics of Complex Networks)
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Reconstructing Networks (Elements in the Structure and Dynamics of Complex Networks)
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Reconstructing Networks
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This Element provides an overview of the ideas, methods and techniques to deal with the problem of missing information in complex networks datasets.Inhaltsverzeichnis1. Introduction 2. Network reconstruction at the macroscale 3. Ne. Seller Inventory # 497431935
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Reconstructing Networks (Paperback)
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Cambridge University Press, Cambridge, 2021
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ISBN 13: 9781108726818
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Paperback. Condition: new. Paperback. Complex networks datasets often come with the problem of missing information: interactions data that have not been measured or discovered, may be affected by errors, or are simply hidden because of privacy issues. This Element provides an overview of the ideas, methods and techniques to deal with this problem and that together define the field of network reconstruction. Given the extent of the subject, the authors focus on the inference methods rooted in statistical physics and information theory. The discussion is organized according to the different scales of the reconstruction task, that is, whether the goal is to reconstruct the macroscopic structure of the network, to infer its mesoscale properties, or to predict the individual microscopic connections. This Element provides an overview of the ideas, methods and techniques to deal with the problem of missing information in complex networks datasets. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781108726818
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