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213.455  Articles
1 of 21.347 pages  |  10  records  |  more records»
DNA gel electrophoresis plays an important role in the development of science. However, the process of manually analyzing DNA size is still relatively difficult, time-consuming, and often results an error. This study proposed electrophoresis process using... see more

In this paper we show that for any spatial dimension the renormalized self-intersection local times of a certain Gaussian process defined by indefinite Wiener integral exist as Hida distributions. An explicit expression for the chaos decomposition in term... see more

The determination of seismic liquefaction potential of soil is an imperative task in earthquake engineering. This article adopts Gaussian Process Regression (GPR) for determination of amount of strain energy required to induce liquefaction. Effective mean... see more

In recent years, environmental pollution has become more and more serious, especially water pollution. In this study, the method of Gaussian process regression was used to build a prediction model for the sulphate content of lakes using several water qual... see more

This article briefly introduces Gaussian processes as a new approach for modelling time series in the field of blazar physics. In the second part of the paper, recent results from an application of GP modelling to the multi-wavelength light curves of the ... see more

Within the Bayesian framework, we utilize Gaussian processes for parametric studies of long running computer codes. Since the simulations are expensive, it is necessary to exploit the computational budget in the best possible manner. Employing the sum ove... see more

In this paper, we obtain an integral formula for the rate distortion function (RDF) of any Gaussian asymptotically wide sense stationary (AWSS) vector process. Applying this result, we also obtain an integral formula for the RDF of Gaussian moving average... see more

In this paper, we examine two widely-used approaches, the polynomial chaos expansion (PCE) and Gaussian process (GP) regression, for the development of surrogate models. The theoretical differences between the PCE and GP approximations are discussed. A st... see more

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. If for a few input parameter settings an output data... see more

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