Dynamics On and Of Complex Networks III [E-Book] : Machine Learning and Statistical Physics Approaches / edited by Fakhteh Ghanbarnejad, Rishiraj Saha Roy, Fariba Karimi, Jean-Charles Delvenne, Bivas Mitra.
This book bridges the gap between advances in the communities of computer science and physics--namely machine learning and statistical physics. It contains diverse but relevant topics in statistical physics, complex systems, network theory, and machine learning. Examples of such topics are: predicti...
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Personal Name(s): | Delvenne, Jean-Charles, editor |
Ghanbarnejad, Fakhteh, editor / Karimi, Fariba, editor / Mitra, Bivas, editor / Saha Roy, Rishiraj, editor | |
Edition: |
1st edition 2019. |
Imprint: |
Cham :
Springer,
2019
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Physical Description: |
X, 244 pages 76 illustrations, 68 illustrations in color (online resource) |
Note: |
englisch |
ISBN: |
9783030146832 |
DOI: |
10.1007/978-3-030-14683-2 |
Series Title: |
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Springer Proceedings in Complexity
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Subject (LOC): |
This book bridges the gap between advances in the communities of computer science and physics--namely machine learning and statistical physics. It contains diverse but relevant topics in statistical physics, complex systems, network theory, and machine learning. Examples of such topics are: predicting missing links, higher-order generative modeling of networks, inferring network structure by tracking the evolution and dynamics of digital traces, recommender systems, and diffusion processes. The book contains extended versions of high-quality submissions received at the workshop, Dynamics On and Of Complex Networks (doocn.org), together with new invited contributions. The chapters will benefit a diverse community of researchers. The book is suitable for graduate students, postdoctoral researchers and professors of various disciplines including sociology, physics, mathematics, and computer science. |