English
Related papers

Related papers: Quantifying synergistic mutual information

200 papers

When two variables are related by a known function, the coefficient of determination (denoted $R^2$) measures the proportion of the total variance in the observations that is explained by that function. This quantifies the strength of the…

Applications · Statistics 2013-03-11 Ben Murrell , Daniel Murrell , Hugh Murrell

Randomness in scientific estimation is generally assumed to arise from unmeasured or uncontrolled factors. However, when combining subjective probability estimates, heterogeneity stemming from people's cognitive or information diversity is…

Methodology · Statistics 2015-05-28 Ville Satopää , Robin Pemantle , Lyle Ungar

Quantum mechanics predicts the joint probability distributions of the outcomes of simultaneous measurements of commuting observables, but the current formulation lacks the operational definition of simultaneous measurements. In order to…

Quantum Physics · Physics 2009-11-06 Masanao Ozawa

We provide a theory independent framework to quantify coherence. In comparison with Bell's theory independent approach to quantum nonlocality, we characterize a general coherence phenomenon with statistics arising from sequential…

Quantum Physics · Physics 2018-02-02 Liang-Liang Sun , Fei-Lei Xiong , Sixia Yu , Zeng-Bing Chen

The task of manipulating correlated random variables in a distributed setting has received attention in the fields of both Information Theory and Computer Science. Often shared correlations can be converted, using a little amount of…

Information Theory · Computer Science 2019-10-03 Madhu Sudan , Himanshu Tyagi , Shun Watanabe

Information theory is a powerful framework for quantifying complexity, uncertainty, and dynamical structure in time-series data, with widespread applicability across disciplines such as physics, finance, and neuroscience. However, the…

Information Theory · Computer Science 2026-01-26 Annie G. Bryant , Oliver M. Cliff , James M. Shine , Ben D. Fulcher , Joseph T. Lizier

Applying a machine learning model for decision-making in the real world requires to distinguish what the model knows from what it does not. A critical factor in assessing the knowledge of a model is to quantify its predictive uncertainty.…

Machine Learning · Computer Science 2023-11-15 Kajetan Schweighofer , Lukas Aichberger , Mykyta Ielanskyi , Sepp Hochreiter

Historically, the element of uncertainty in quantum mechanics has been expressed through mathematical identities called uncertainty relations, a great many of which continue to be discovered. These relations use diverse measures to quantify…

Quantum Physics · Physics 2016-03-16 Varun Narasimhachar , Alireza Poostindouz , Gilad Gour

Estimating the mutual information from samples from a joint distribution is a challenging problem in both science and engineering. In this work, we realize a variational bound that generalizes both discriminative and generative approaches.…

Machine Learning · Statistics 2023-06-05 Marco Federici , David Ruhe , Patrick Forré

Data cohesion, a recently introduced measure inspired by social interactions, uses distance comparisons to assess relative proximity. In this work, we provide a collection of results which can guide the development of cohesion-based methods…

Social and Information Networks · Computer Science 2023-08-08 Katherine E. Moore

Redundancy represents a strategy for achieving high availability. However, various factors, known as singleness factors, necessitate corresponding redundancy measures. The absence of a systematic approach for identifying these singleness…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-10-10 Hong Su

The recently established resource theory of quantum coherence allows for a quantitative understanding of the superposition principle, with applications reaching from quantum computing to quantum biology. While different quantifiers of…

Complexity is a multi-faceted phenomenon, involving a variety of features including disorder, nonlinearity, and self-organisation. We use a recently developed rigorous framework for complexity to understand measures of complexity. We…

Adaptation and Self-Organizing Systems · Physics 2020-09-22 Karoline Wiesner , James Ladyman

Information theory is a practical and theoretical framework developed for the study of communication over noisy channels. Its probabilistic basis and capacity to relate statistical structure to function make it ideally suited for studying…

Neurons and Cognition · Quantitative Biology 2015-01-09 Robin A. A. Ince , Simon R. Schultz , Stefano Panzeri

We present a new measure of entanglement for mixed states. It can be approximately computable for every state and can be used to quantify all different types of multipartite entanglement. We show that it satisfies the usual properties of a…

Quantum Physics · Physics 2007-05-23 Fernando G. S. L. Brandao , Reinaldo O. Vianna

The notion of machine companions has long been embedded in social-technological imaginaries. Recent advances in AI have moved those media musings into believable sociality manifested in interfaces, robotic bodies, and devices. Those…

Human-Computer Interaction · Computer Science 2026-03-02 Jaime Banks , Zhixin Li

Partial information decomposition (PID) of the multivariate mutual information describes the distinct ways in which a set of source variables contains information about a target variable. The groundbreaking work of Williams and Beer has…

Information Theory · Computer Science 2021-03-31 Abdullah Makkeh , Aaron J. Gutknecht , Michael Wibral

Quantifying coherence is an essential endeavour for both quantum foundations and quantum technologies. Here the robustness of coherence is defined and proven a full monotone in the context of the recently introduced resource theories of…

The concept of correlation appears straightforward: measurement outcomes coincide, and patterns emerge. For any record of events, the coefficients are uniquely determined. Thus, if correlations change spontaneously, as seen in quantum…

General Physics · Physics 2025-12-22 Ghenadie N. Mardari

This paper develops new methodology, together with related theories, for combining information from independent studies through confidence distributions. A formal definition of a confidence distribution and its asymptotic counterpart (i.e.,…

Statistics Theory · Mathematics 2007-06-13 Kesar Singh , Minge Xie , William E. Strawderman