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Information Entropy Measures for Evaluation of Reliability of Deep Neural Network Results
Entropy, 2023 Deep neural networks (DNN) try to analyze given data, to come up with decisions regarding the inputs. The decision-making process of the DNN model is not entirely transparent.
Elakkat D. Gireesh, Varadaraj P. Gurupur
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Information Measures for Entropy and Symmetry
CoRR, 2022 Entropy and information can be considered dual: entropy is a measure of the subspace defined by the information constraining the given ambient space. Negative entropies, arising in naïve extensions of the definition of entropy from discrete to continuous settings, are byproducts of the use of probabilities, which only work in the discrete case by a ...
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Towards information inequalities for generalized graph entropies. [PDF]
PLoS ONE, 2012 In this article, we discuss the problem of establishing relations between information measures for network structures. Two types of entropy based measures namely, the Shannon entropy and its generalization, the Rényi entropy have been considered for this
Lavanya Sivakumar, Matthias Dehmer
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Gaze Information Channel in Van Gogh’s Paintings
Entropy, 2020 This paper uses quantitative eye tracking indicators to analyze the relationship between images of paintings and human viewing. First, we build the eye tracking fixation sequences through areas of interest (AOIs) into an information channel, the gaze ...
Qiaohong Hao +4 more
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Exponential Entropy for Simplified Neutrosophic Sets and Its Application in Decision Making
Entropy, 2018 Entropy is one of many important mathematical tools for measuring uncertain/fuzzy information. As a subclass of neutrosophic sets (NSs), simplified NSs (including single-valued and interval-valued NSs) can describe incomplete, indeterminate, and ...
Jun Ye, Wenhua Cui
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On Entropy of Some Fractal Structures
Fractal and Fractional, 2023 Shannon entropy, also known as information entropy or entropy, measures the uncertainty or randomness of probability distribution. Entropy is measured in bits, quantifying the average amount of information required to identify an event from the ...
Haleemah Ghazwani +3 more
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Entropy, 2005 : Entropy is a basic physical quantity that led to various, and sometimes apparently conflicting interpretations. It has been successively assimilated to different concepts such as disorder and information.
Jean-Bernard Brissaud
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Rényi Entropies of Dynamical Systems: A Generalization Approach [PDF]
Journal of Mahani Mathematical Research, 2023 Entropy measures have received considerable attention in quantifying the structural complexity of real-world systems and are also used as measures of information obtained from a realization of the considered experiments. In the present study, new notions
Zahra Eslami Giski +2 more
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Properties of Risk Measures of Generalized Entropy in Portfolio Selection
Entropy, 2017 This paper systematically investigates the properties of six kinds of entropy-based risk measures: Information Entropy and Cumulative Residual Entropy in the probability space, Fuzzy Entropy, Credibility Entropy and Sine Entropy in the fuzzy space, and ...
Rongxi Zhou +3 more
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MAXIMIZABLE INFORMATIONAL ENTROPY AS A MEASURE OF PROBABILISTIC UNCERTAINTY [PDF]
International Journal of Modern Physics B, 2010 In this work, we consider a recently proposed entropy S defined by a variational relationship [Formula: see text] as a measure of uncertainty of random variable x. The entropy defined in this way underlies an extension of virtual work principle [Formula: see text] leading to the maximum entropy [Formula: see text].
Ou, C. J. +6 more
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