Beyond Moments: Extending the Maximum Entropy Principle to Feature Distribution Constraints [PDF]
Entropy, 2018 The maximum entropy principle introduced by Jaynes proposes that a data distribution should maximize the entropy subject to constraints imposed by the available knowledge.
Paul M. Baggenstoss
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On the Entropy and the Maximum Entropy Principle of Uncertain Variables [PDF]
Entropy, 2023 A new variance formula is developed using the generalized inverse of an increasing function. Based on the variance formula, a new entropy formula for any uncertain variable is provided.
Yujun Liu, Guanzhong Ma
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The maximum entropy principle for compositional data [PDF]
BMC Bioinformatics, 2022 Background Compositional systems, represented as parts of some whole, are ubiquitous. They encompass the abundances of proteins in a cell, the distribution of organisms in nature, and the stoichiometry of the most basic chemical reactions.
Corey Weistuch +3 more
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Remarks on the Maximum Entropy Principle with Application to the Maximum Entropy Theory of Ecology [PDF]
Entropy, 2017 In the first part of the paper we work out the consequences of the fact that Jaynes’ Maximum Entropy Principle, when translated in mathematical terms, is a constrained extremum problem for an entropy function H ( p ) expressing the uncertainty ...
Marco Favretti
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A Quantile General Index Derived from the Maximum Entropy Principle [PDF]
Entropy, 2022 We propose a linear separation method of multivariate quantitative data in such a way that the average of each variable in the positive group is larger than that of the negative group. Here, the coefficients of the separating hyperplane are restricted to
Tomonari Sei
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Calibration Invariance of the MaxEnt Distribution in the Maximum Entropy Principle [PDF]
Entropy, 2021 The maximum entropy principle consists of two steps: The first step is to find the distribution which maximizes entropy under given constraints. The second step is to calculate the corresponding thermodynamic quantities.
Jan Korbel
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Combining experiments and simulations using the maximum entropy principle. [PDF]
PLoS Computational Biology, 2014 A key component of computational biology is to compare the results of computer modelling with experimental measurements. Despite substantial progress in the models and algorithms used in many areas of computational biology, such comparisons sometimes ...
Wouter Boomsma +2 more
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Timeless Histories: Quantum Measurement and the Maximum Entropy Principle [PDF]
EntropyThe quantum measurement problem, i.e., the apparent conflict between unitary quantum evolution and non-unitary, stochastic wave-function collapse, remains unresolved a century after the formulation of quantum mechanics.
Alexei V. Tkachenko
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Entropy, 2017 The determination of the probability distribution function (PDF) of uncertain input and model parameters in engineering application codes is an issue of importance for uncertainty quantification methods. One of the approaches that can be used for the PDF
José-Luis Muñoz-Cobo +4 more
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Maximum entropy principle based estimation of performance distribution in queueing theory. [PDF]
PLoS ONE, 2014 In related research on queuing systems, in order to determine the system state, there is a widespread practice to assume that the system is stable and that distributions of the customer arrival ratio and service ratio are known information. In this study,
Dayi He, Ran Li, Qi Huang, Ping Lei
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