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This chapter provides a comprehensive and self-contained discussion of the most recent developments of information theory of networks. Maximum entropy models of networks are the least biased ensembles enforcing a set of constraints and are…

Disordered Systems and Neural Networks · Physics 2022-06-14 Ginestra Bianconi

Functional connectivity is a fundamental property of neural networks that quantifies the segregation and integration of information between cortical areas. Due to mathematical complexity, a theory that could explain how the parameters of…

Neurons and Cognition · Quantitative Biology 2016-05-27 Diego Fasoli , Anna Cattani , Stefano Panzeri

The major problem in information theoretic analysis of neural responses and other biological data is the reliable estimation of entropy--like quantities from small samples. We apply a recently introduced Bayesian entropy estimator to…

Data Analysis, Statistics and Probability · Physics 2009-09-29 Ilya Nemenman , William Bialek , Rob de Ruyter van Steveninck

In recent years, the theory and application of complex networks have been quickly developing in a markable way due to the increasing amount of data from real systems and to the fruitful application of powerful methods used in statistical…

Physics and Society · Physics 2014-05-23 Enys Mones

Complex networks are the subject of fundamental interest from the scientific community at large. Several metrics have been introduced to characterize the structure of these networks, such as the degree distribution, degree correlation, path…

Physics and Society · Physics 2019-01-14 Francesco Sorrentino , Abu Bakar Siddique , Louis M. Pecora

Correlations between two variables of a high-dimensional system can be indicative of an underlying interaction, but can also result from indirect effects. Inverse Ising inference is a method to distinguish one from the other. Essentially,…

Populations and Evolution · Quantitative Biology 2014-12-10 Benedikt Obermayer , Erel Levine

Several recent works have empirically observed that Convolutional Neural Nets (CNNs) are (approximately) invertible. To understand this approximate invertibility phenomenon and how to leverage it more effectively, we focus on a theoretical…

Machine Learning · Statistics 2017-05-25 Anna C. Gilbert , Yi Zhang , Kibok Lee , Yuting Zhang , Honglak Lee

This research is about studying and comparing two different ways of building complex networks. The main goal of our study is to find an effective way to build networks, particularly when we have fewer observations than variables. We…

Methodology · Statistics 2014-09-10 Lina D. Thomas , Victor Fossaluza , Anatoly Yambartsev

The paper is devoted to the effects of superconducting pairing in small metallic grains. It turns out that at strong superconducting coupling and in the limit of large Thouless conductance one can explicitly determine the low energy…

Strongly Correlated Electrons · Physics 2009-02-06 Emil A. Yuzbashyan , Alexander A. Baytin , Boris L. Altshuler

Networks effectively capture interactions among components of complex systems, and have thus become a mainstay in many scientific disciplines. Growing evidence, especially from biology, suggest that networks undergo changes over time, and…

Methodology · Statistics 2020-03-10 Ali Shojaie

The dynamical behaviour of a weakly diluted fully-inhibitory network of pulse-coupled spiking neurons is investigated. Upon increasing the coupling strength, a transition from regular to stochastic-like regime is observed. In the…

Disordered Systems and Neural Networks · Physics 2007-05-23 R. Zillmer , R. Livi , A. Politi , A. Torcini

A dynamical system is controllable if by imposing appropriate external signals on a subset of its nodes, it can be driven from any initial state to any desired state in finite time. Here we study the impact of various network…

Physics and Society · Physics 2013-01-16 Márton Pósfai , Yang-Yu Liu , Jean-Jacques Slotine , Albert-László Barabási

When constructing models of the world, we aim for optimal compressions: models that include as few details as possible while remaining as accurate as possible. But which details -- or features measured in data -- should we choose to include…

Quantitative Methods · Quantitative Biology 2025-05-06 David P. Carcamo , Nicholas J. Weaver , Purushottam D. Dixit , Christopher W. Lynn

In this article the problem of reconstructing the pattern of connection between agents from partial empirical data in a macro-economic model is addressed, given a set of behavioral equations. This systemic point of view puts the focus on…

General Economics · Economics 2019-01-30 Aurélien Hazan

The broad abundance of time series data, which is in sharp contrast to limited knowledge of the underlying network dynamic processes that produce such observations, calls for a rigorous and efficient method of causal network inference. Here…

Information Theory · Computer Science 2015-05-19 Jie Sun , Dane Taylor , Erik M. Bollt

We develop two generalizations of contraction theory, namely, semi-contraction and weak-contraction theory. First, using the notion of semi-norm, we propose a geometric framework for semi-contraction theory. We introduce matrix…

Systems and Control · Electrical Eng. & Systems 2020-10-06 Saber Jafarpour , Pedro Cisneros-Velarde , Francesco Bullo

Entropy and information provide natural measures of correlation among elements in a network. We construct here the information theoretic analog of connected correlation functions: irreducible $N$--point correlation is measured by a decrease…

Biological Physics · Physics 2016-09-08 Elad Schneidman , Susanne Still , Michael J. Berry , William Bialek

In social networks, it is conventionally thought that two individuals with more overlapped friends tend to establish a new friendship, which could be stated as homophily breeding new connections. While the recent hypothesis of maximum…

Social and Information Networks · Computer Science 2016-02-17 Jichang Zhao , Xiao Liang , Ke Xu

The recent discovery of universal principles underlying many complex networks occurring across a wide range of length scales in the biological world has spurred physicists in trying to understand such features using techniques from…

Biological Physics · Physics 2015-05-13 Sitabhra Sinha

The study of the weak-ties phenomenon has a long and well documented history, research into the application of this social phenomenon has recently attracted increasing attention. However, further exploration of the reasons behind the…

Physics and Society · Physics 2025-04-30 Ke-ke Shang , Michael Small , Di Yin , Yan Wang , Tong-chen Li