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Related papers: Geometry of Information Integration

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The conventional definition of a topological metric over a space specifies properties that must be obeyed by any measure of "how separated" two points in that space are. Here it is shown how to extend that definition, and in particular the…

Adaptation and Self-Organizing Systems · Physics 2007-10-15 David H. Wolpert

The recent introduction of geometric partition entropy brought a new viewpoint to non-parametric entropy quantification that incorporated the impacts of informative outliers, but its original formulation was limited to the context of a…

Physics and Society · Physics 2024-11-11 C. Tyler Diggans , Abd AlRahman R. AlMomani

A new measure of information in quantum mechanics is proposed which takes into account that for quantum systems the only feature known before an experiment is performed are the probabilities for various events to occur. The sum of the…

Quantum Physics · Physics 2009-11-06 Caslav Brukner , Anton Zeilinger

The ability to integrate information in the brain is considered to be an essential property for cognition and consciousness. Integrated Information Theory (IIT) hypothesizes that the amount of integrated information ($\Phi$) in the brain is…

Neurons and Cognition · Quantitative Biology 2018-04-04 Jun Kitazono , Ryota Kanai , Masafumi Oizumi

The information geometry of the 2-manifold of gamma probability density functions provides a framework in which pseudorandom number generators may be evaluated using a neighbourhood of the curve of exponential density functions. The process…

Computation · Statistics 2009-07-13 C. T. J. Dodson

Smooth entropies are a tool for quantifying resource trade-offs in (quantum) information theory and cryptography. In typical bi- and multi-partite problems, however, some of the sub-systems are often left unchanged and this is not reflected…

Quantum Physics · Physics 2020-07-20 Anurag Anshu , Mario Berta , Rahul Jain , Marco Tomamichel

Intrinsic computation refers to how dynamical systems store, structure, and transform historical and spatial information. By graphing a measure of structural complexity against a measure of randomness, complexity-entropy diagrams display…

Chaotic Dynamics · Physics 2009-11-13 David P. Feldman , Carl S. McTague , James P. Crutchfield

Interaction information is one of the multivariate generalizations of mutual information, which expresses the amount information shared among a set of variables, beyond the information, which is shared in any proper subset of those…

Artificial Intelligence · Computer Science 2017-02-01 AmirEmad Ghassami , Negar Kiyavash

Information-theoretic measures such as relative entropy and correlation are extremely useful when modeling or analyzing the interaction of probabilistic systems. We survey the quantum generalization of 5 such measures and point out some of…

Information Theory · Computer Science 2015-06-02 William Blacoe

Information geometry provides a geometric approach to families of statistical models. The key geometric structures are the Fisher quadratic form and the Amari-Chentsov tensor. In statistics, the notion of sufficient statistic expresses the…

Statistics Theory · Mathematics 2015-05-27 Nihat Ay , Jürgen Jost , Hông Vân Lê , Lorenz Schwachhöfer

The framework of Partial Information Decomposition (PID) unveils complex nonlinear interactions in network systems by dissecting the mutual information (MI) between a target variable and several source variables. While PID measures have…

Data Analysis, Statistics and Probability · Physics 2024-09-23 Chiara Barà , Yuri Antonacci , Marta Iovino , Ivan Lazic , Luca Faes

Information flow or information transfer is an important concept in dynamical systems which has applications in a wide variety of scientific disciplines. In this study, we show that a rigorous formalism can be established in the context of…

Chaotic Dynamics · Physics 2007-10-05 X. San Liang

The paper considers a new quantitative-qualitative proximity measure for the features of information objects, where data enters a common information resource from several sources independently. The goal is to determine the possibility of…

Artificial Intelligence · Computer Science 2026-04-08 Volodymyr Yuzefovych

We study correlation measures for complex systems. First, we investigate some recently proposed measures based on information geometry. We show that these measures can increase under local transformations as well as under discarding…

Adaptation and Self-Organizing Systems · Physics 2012-04-20 Tobias Galla , Otfried Gühne

According to the Integrated Information Theory of Consciousness, consciousness is a fundamental observer-independent property of physical systems, and the measure Phi of integrated information is identical to the quantity or level of…

Neurons and Cognition · Quantitative Biology 2019-02-13 Adam B. Barrett , Pedro A. M. Mediano

Quantifying cooperation or synergy among random variables in predicting a single target random variable is an important problem in many complex systems. We review three prior information-theoretic measures of synergy and introduce a novel…

Information Theory · Computer Science 2014-04-02 Virgil Griffith , Christof Koch

We develop a language for describing the relationship among observations, mathematical models, and the underlying principles from which they are derived. Using Information Geometry, we consider geometric properties of statistical models for…

Data Analysis, Statistics and Probability · Physics 2016-07-14 Mark K. Transtrum , Gus Hart , Peng Qiu

A novel measure, quantumness of correlations is introduced here for bipartite states, by incorporating the required measurement scheme crucial in defining any such quantity. Quantumness coincides with the previously proposed measures in…

Quantum Physics · Physics 2008-04-20 A. R. Usha Devi , A. K. Rajagopal

The method of geometric harmonics is adapted to the situation of incomplete data by means of the iterated geometric harmonics (IGH) scheme. The method is tested on natural and synthetic data sets with 50--500 data points and dimensionality…

Machine Learning · Computer Science 2014-11-05 Chad Eckman , Jonathan A. Lindgren , Erin P. J. Pearse , David J. Sacco , Zachariah Zhang

A central challenge in cellular signal processing is understanding how biochemical networks perform reliably despite molecular noise. Traditionally, mutual information has been widely used to quantify signaling fidelity, capturing how well…

Biological Physics · Physics 2026-02-23 Mintu Nandi , Sosuke Ito