Results 11 to 20 of about 1,258,060 (324)
An automation system for vehicle driveability evaluation using machine learning
Nihon Kikai Gakkai ronbunshu, 2022 The drivability is one of the important aspects of vehicle dynamic performances. To ensure quality of the drivability performance, comprehensive screening evaluation is necessary by controlling both complicated driver operation and vehicle behavior ...
Hisashi TAJIMA +4 more
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Gaussian process hydrodynamics
Applied Mathematics and Mechanics, 2023 AbstractWe present a Gaussian process (GP) approach, called Gaussian process hydrodynamics (GPH) for approximating the solution to the Euler and Navier-Stokes (NS) equations. Similar to smoothed particle hydrodynamics (SPH), GPH is a Lagrangian particle-based approach that involves the tracking of a finite number of particles transported by a flow ...
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Revisiting cosmography via Gaussian process
European Physical Journal C: Particles and Fields, 2023 In this paper, we revisit the kinematical state of our Universe via the cosmographic approach by using Gaussian process, where the minimum assumption is the cosmological principle, i.e. the Friedmann–Lemaître–Robertson–Walker metric.
Jinyi Liu +3 more
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Recurrent Gaussian processes [PDF]
, 2015 Published as a conference paper at ICLR 2016.
Mattos, C.L.C. +5 more
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Gaussian Processes and Gaussian Measures
The Annals of Mathematical Statistics, 1972 The subject of this paper is the study of the correspondence between Gaussian processes with paths in linear function spaces and Gaussian measures on function spaces. For the function spaces $C(I), C^n\lbrack a, b\rbrack, AC\lbrack a, b\rbrack$ and $L_2(T, \mathscr{A}, \nu)$ it is shown that if a Gaussian process has paths in these spaces then it ...
Rajput, Balram S., Cambanis, Stamatis
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Hierarchical Gaussian process mixtures for regression [PDF]
, 2004 As a result of their good performance in practice and their desirable analytical properties, Gaussian process regression models are becoming increasingly of interest in statistics, engineering and other fields.
A. Gelman +17 more
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Design Support of function of brassiere cup using gaussian process regression
Nihon Kikai Gakkai ronbunshu, 2021 A method to design the function of the brassiere cup shape as developable surfaces and its developed shape using Gaussian Process Regression is proposed.
Kotaro YOSHIDA +3 more
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Gaussian process model based predictive control [PDF]
, 2003 Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of non-linear dynamic systems. The Gaussian processes can highlight areas of the input space where prediction quality is poor, due to the lack ...
, +4 more
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Sequentially Estimating the Approximate Conditional Mean Using Extreme Learning Machines
Entropy, 2020 This study examined the extreme learning machine (ELM) applied to the Wald test statistic for the model specification of the conditional mean, which we call the WELM testing procedure.
Lijuan Huo, Jin Seo Cho
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Recent developments in empirical dynamic modelling
Methods in Ecology and Evolution, 2023 Ecosystems are complex and sparsely observed making inference and prediction challenging. Empirical dynamic modelling (EDM) circumvents the need for a parametric model and complete observations of all system variables.
Stephan B. Munch +2 more
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