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Palm distributions for log Gaussian Cox processes [PDF]
, 2015 This paper establishes a remarkable result regarding Palmdistributions for a log Gaussian Cox process: the reduced Palmdistribution for a log Gaussian Cox process is itself a log Gaussian Coxprocess which only differs from the original log Gaussian Cox ...
Coeurjolly, Jean-François +2 more
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Physical Review D, 2012 Gaussian processes provide a method for extracting cosmological information from observations without assuming a cosmological model. We carry out cosmography -- mapping the time evolution of the cosmic expansion -- in a model-independent manner using kinematic variables and a geometric probe of cosmology.
Shafieloo, Arman +2 more
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Global Optimization Employing Gaussian Process-Based Bayesian Surrogates
Entropy, 2018 The simulation of complex physics models may lead to enormous computer running times. Since the simulations are expensive it is necessary to exploit the computational budget in the best possible manner.
Roland Preuss, Udo von Toussaint
doaj +1 more source
Applied Sciences, 2019 Precise prediction of short-term electric load demand is the key for developing power market strategies. Due to the dynamic environment of short-term load forecasting, probabilistic forecasting has become the center of attention for its ability of ...
Zhengmin Kong +3 more
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Suspended sediment load modeling by machine learning algorithms in low and high discharge periods (Case study: Kashkan watershed) [PDF]
مدلسازی و مدیریت آب و خاک, 2023 IntroductionSediment that moves with water is called suspended sediment, and the amount of suspended sediment material that passes through a river section in a certain period of time is called suspended load.
Nasrin Beiranvand +2 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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Continuity of Gaussian Processes [PDF]
The Annals of Probability, 1986 The author first gives a generalization of \textit{M. B. Marcus} and \textit{L. A. Shepp}'s [Proc. Sixth Berkeley Sympos. math. Statist. Probab., Univ. Calif. 1970, 2, 423-441 (1972; Zbl 0379.60040)] theorem on the equivalence between sample continuity of a Gaussian process defined on a compact subset of a metric space, and a.s.
openaire +3 more sources
Power Load Forecasting Method Based on MT-BSGP
Journal of Harbin University of Science and Technology, 2021 In order to forecast short-term household power load，a power load forecasting method based on multi-task Bayesian spatiotemporal Gaussian process ( MT-BSGP) is proposed.
LI Zhi-yong +5 more
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Modelling of Infiltration Rate in Different Soil Textures using Soft Computing Techniques in Kashkan Watershed, Lorestan Province [PDF]
پژوهشهای آبخیزداری, 2022 Infiltration is one of the most parameters of hydrology that plays a fundamental role in streamflow, groundwater recharge, subsurface flow, and surface and subsurface water quality and quantity.
Leili Soleimani +2 more
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Massively parallel approximate Gaussian process regression [PDF]
, 2014 We explore how the big-three computing paradigms -- symmetric multi-processor (SMC), graphical processing units (GPUs), and cluster computing -- can together be brought to bare on large-data Gaussian processes (GP) regression problems via a careful ...
Gramacy, Robert +3 more
core +4 more sources