Results 41 to 50 of about 59,568 (301)
Statistical cosymplectic manifolds and their submanifolds
پژوهشهای ریاضی, 2022 Introduction Let p(x,ζ) be the set of parametric probability distribution with parameter ζ=ζ1,…,ζn∊Rn. This set is called a statistical model or manifold. The distance between two points is measured by the Fisher metric. In general, statistical manifolds
Mohammad Bagher Kazemi, Shiva Salahvarzi
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Application of Statistical K-Means Algorithm for University Academic Evaluation
Entropy, 2022 With the globalization of higher education, academic evaluation is increasingly valued by the scientific and educational circles. Although the number of published papers of academic evaluation methods is increasing, previous research mainly focused on ...
Daohua Yu +4 more
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Learning on dynamic statistical manifolds
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2020 Hyperbolic balance laws with uncertain (random) parameters and inputs are ubiquitous in science and engineering. Quantification of uncertainty in predictions derived from such laws, and reduction of predictive uncertainty via data assimilation, remain an open challenge.
F. Boso, D. M. Tartakovsky
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Basic inequalities for statistical submanifolds in Golden-like statistical manifolds
Open Mathematics, 2022 In this paper, we introduce and study Golden-like statistical manifolds. We obtain some basic inequalities for curvature invariants of statistical submanifolds in Golden-like statistical manifolds.
Lone Mohamd Saleem +3 more
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Mathematics, 2022 The geometry of Hessian manifolds is a fruitful branch of physics, statistics, Kaehlerian and affine differential geometry. The study of inequalities for statistical submanifolds in Hessian manifolds of constant Hessian curvature was truly initiated in ...
Aliya Naaz Siddiqui +2 more
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Affine Differential Geometric Control Tools for Statistical Manifolds
Mathematics, 2021 The paper generalizes and extends the notions of dual connections and of statistical manifold, with and without torsion. Links with the deformation algebras and with the Riemannian Rinehart algebras are established.
Iulia-Elena Hirica +3 more
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Manifold Statistics for Essential Matrices [PDF]
, 2012 Riemannian geometry allows for the generalization of statistics designed for Euclidean vector spaces to Riemannian manifolds. It has recently gained popularity within computer vision as many relevant parameter spaces have such a Riemannian manifold structure. Approaches which exploit this have been shown to exhibit improved efficiency and accuracy. The
Dubbelman, G., Dorst, L., Pijls, H.
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Extremities for statistical submanifolds in Кenmotsu statistical manifolds
Filomat, 2021 Kenmotsu geometry is a valuable part of contact geometry with nice applications in other fields such as theoretical physics. In this article, we study the statistical counterpart of a Kenmotsu manifold, that is, Kenmotsu statistical manifold with some related examples.
Siddiqui, Aliya Naaz +2 more
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Mathematics, 2022 In this study, some identities involving the Riemannian curvature invariants are presented on lightlike hypersurfaces of a statistical manifold in the Lorentzian settings. Several inequalities characterizing lightlike hypersurfaces are obtained.
Oğuzhan Bahadır +3 more
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A Sequence of Escort Distributions and Generalizations of Expectations on q-Exponential Family
Entropy, 2016 In the theory of complex systems, long tailed probability distributions are often discussed. For such a probability distribution, a deformed expectation with respect to an escort distribution is more useful than the standard expectation.
Hiroshi Matsuzoe
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