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Approximations of the Reproducing Kernel Hilbert Space (RKHS) Embedding Method over Manifolds [PDF]
IEEE Conference on Decision and Control, 2020 The reproducing kernel Hilbert space (RKHS) embedding method is a recently introduced estimation approach that seeks to identify the unknown or uncertain function in the governing equations of a nonlinear set of ordinary differential equations (ODEs ...
Jia Guo +2 more
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Optimal Penalized Function-on-Function Regression under a Reproducing Kernel Hilbert Space Framework. [PDF]
J Am Stat Assoc, 2018 Many scientific studies collect data where the response and predictor variables are both functions of time, location, or some other covariate. Understanding the relationship between these functional variables is a common goal in these studies.
Sun X, Du P, Wang X, Ma P.
europepmc +3 more sources
Journal of Taibah University for Science, 2019 Reproducing kernel Hilbert space method is given for the solution of generalized Kuramoto–Sivashinsky equation. Reproducing kernel functions are obtained to get the solution of the generalized Kuramoto–Sivashinsky equation.
Ali Akgül, Ebenezer Bonyah
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Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations [PDF]
Statistics and computing, 2015 We describe a method to perform functional operations on probability distributions of random variables. The method uses reproducing kernel Hilbert space representations of probability distributions, and it is applicable to all operations which can be ...
Bernhard Schölkopf +4 more
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Advances in Difference Equations, 2018 In this article, we propose a new method that determines an efficient numerical procedure for solving second-order fuzzy Volterra integro-differential equations in a Hilbert space.
Ghaleb N. Gumah +3 more
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Single image super-resolution via an iterative reproducing kernel Hilbert space method. [PDF]
IEEE Trans Circuits Syst Video Technol, 2016 Deng LJ, Guo W, Huang TZ.
europepmc +2 more sources
Soft and hard classification by reproducing kernel Hilbert space methods. [PDF]
Proc Natl Acad Sci U S A, 2002 Wahba G.
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Reproducing Kernel Hilbert Space Approach to Multiresponse Smoothing Spline Regression Function
Symmetry, 2022 In statistical analyses, especially those using a multiresponse regression model approach, a mathematical model that describes a functional relationship between more than one response variables and one or more predictor variables is often involved.
Budi Lestari +3 more
semanticscholar +1 more source
Chinese Journal of Mechanical Engineering, 2021 Deep learning algorithms based on neural networks make remarkable achievements in machine fault diagnosis, while the noise mixed in measured signals harms the prediction accuracy of networks.
Baoxuan Zhao +5 more
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Discovering Causal Structure with Reproducing-Kernel Hilbert Space ε-Machines [PDF]
Chaos, 2020 We merge computational mechanics' definition of causal states (predictively equivalent histories) with reproducing-kernel Hilbert space (RKHS) representation inference.
N. Brodu, J. Crutchfield
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