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Dynamics On and Of Complex Networks III

Machine Learning and Statistical Physics Approaches

Rishiraj Saha Roy (Hrsg.), Bivas Mitra (Hrsg.), Fariba Karimi (Hrsg.), Fakhteh Ghanbarnejad (Hrsg.), Jean-Charles Delvenne (Hrsg.)

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Springer International Publishing img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Theoretische Physik

Beschreibung

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.

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Schlagwörter

inferring network structure, information diffusion, computational social sciences, data-driven science, modeling and theory building, complexity, nodes in empirical networks, generating random networks, nonlinear dynamics on networks, community detection