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Basic principles of statistical inference are commonly violated in network data analysis. Under the current approach, it is often impossible to identify a model that accommodates known empirical behaviors, possesses crucial inferential…

Statistics Theory · Mathematics 2017-01-02 Harry Crane , Walter Dempsey

Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior…

Statistical Mechanics · Physics 2015-06-24 M. E. J. Newman

In order to maintain consistent quality of service, computer network engineers face the task of monitoring the traffic fluctuations on the individual links making up the network. However, due to resource constraints and limited access, it…

Applications · Statistics 2010-05-26 Joel Vaughan , Stilian A. Stoev , George Michailidis

In this paper, we provide a review on both fundamentals of social networks and latent space modeling. The former discusses important topics related to network description, including vertex characteristics and network structure; whereas the…

Social and Information Networks · Computer Science 2020-12-07 Juan Sosa , Lina Buitrago

The adaptive processing of graph data is a long-standing research topic which has been lately consolidated as a theme of major interest in the deep learning community. The snap increase in the amount and breadth of related research has come…

Machine Learning · Computer Science 2020-06-16 Davide Bacciu , Federico Errica , Alessio Micheli , Marco Podda

A general theoretical framework based on group-subgroup and group-supergroup relations is proposed to describe and to derive interpenetrating nets.

Materials Science · Physics 2018-05-07 Igor A. Baburin

Networks are models representing relationships between entities. Often these relationships are explicitly given, or we must learn a representation which generalizes and predicts observed behavior in underlying individual data (e.g.…

Social and Information Networks · Computer Science 2017-09-19 Ivan Brugere , Chris Kanich , Tanya Y. Berger-Wolf

Introduction to the Special Issue: Genome-Wide Association Studies

Methodology · Statistics 2010-10-25 Gang Zheng , Jonathan Marchini , Nancy L. Geller

Based on a simple example, it is explained how the homological analysis may be applied for modeling of the electric circuits. The homological branch, mesh and nodal analyses are presented. Geometrical interpretations are given.

Mathematical Physics · Physics 2015-04-06 Eugen Paal , Märt Umbleja

Online Appendix to: "Analyzing Control Flow Information to Improve the Effectiveness of Process Model Matching Techniques" by the same authors.

Other Computer Science · Computer Science 2017-07-06 Christopher Klinkmüler , Ingo Weber

Many economic activities are embedded in networks: sets of agents and the (often) rivalrous relationships connecting them to one another. Input sourcing by firms, interbank lending, scientific research, and job search are four examples,…

Econometrics · Economics 2019-12-16 Bryan S. Graham

Now that spike trains from many neurons can be recorded simultaneously, there is a need for methods to decode these data to learn about the networks that these neurons are part of. One approach to this problem is to adjust the parameters of…

Quantitative Methods · Quantitative Biology 2011-06-10 John Hertz , Yasser Roudi , Joanna Tyrcha

Network datasets typically exhibit certain types of statistical dependencies, such as within-dyad correlation, row and column heterogeneity, and third-order dependence patterns such as transitivity and clustering. The first two of these can…

Methodology · Statistics 2018-07-24 Peter D. Hoff

The science of networks has revolutionised research into the dynamics of interacting elements. It could be argued that epidemiology in particular has embraced the potential of network theory more than any other discipline. Here we review…

Generalized mutual entropy is defined for networks and applied for analysis of complex network structures. The method is tested for the case of computer simulated scale free networks, random networks, and their mixtures. The possible…

Disordered Systems and Neural Networks · Physics 2009-11-13 V. Gudkov , V. Montealegre

Descriptive and inferential social network analysis has become common in public administration studies of network governance and management. A large literature has developed in two broad categories: antecedents of network structure, and…

Social and Information Networks · Computer Science 2024-09-02 Travis A. Whetsell , Michael D. Siciliano

This is a natural generalization of the previous work by Dan, "Modeling and Simulation of Diffusion Phenomena on Social Networks," to appear in The proceedings of 2011 Third International Conference on Computer Modeling and Simulation. In…

Social and Information Networks · Computer Science 2011-03-14 Yuya Dan

In this work, we present preliminary results demonstrating the ability to recover a significant amount of information about secret model inputs given only very limited access to model outputs and the ability evaluate the model on additive…

Computer Vision and Pattern Recognition · Computer Science 2019-04-12 Nick Moran , Chiraag Juvekar

Currently, the world is witnessing a mounting avalanche of data due to the increasing number of mobile network subscribers, Internet websites, and online services. This trend is continuing to develop in a quick and diverse manner in the…

Networking and Internet Architecture · Computer Science 2018-02-12 Mohammed S. Hadi , Ahmed Q. Lawey , Taisir E. H. El-Gorashi , Jaafar M. H. Elmirghani

This article provides a selective review on the recent literature on econometric models of network formation. The survey starts with a brief exposition on basic concepts and tools for the statistical description of networks. I then offer a…

Econometrics · Economics 2020-01-14 Aureo de Paula