Gaussian process
A GAUSSIAN PROCESS BASED MULTI-PERSON INTERACTION MODEL
... A Gaussian Process is a stochastic process in which any finite subset of random variables has a Gaussian joint ...is Gaussian, which favours their application in the context of ...
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Correction: Bayesian Sensitivity Analysis of a Cardiac Cell Model Using a Gaussian Process Emulator.
... This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, prov[r] ...
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Estimating Multiple Step Shifts in a Gaussian Process Mean with an Application to Phase I Control Chart Analysis
... underlying process which leads to parametric, semiparametric or nonparametric methods of change point detection, ...statistical process monitoring, statistical control theory, pattern recognition, signal ...
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Predicting Market Impact Costs Using Nonparametric Machine Learning Models.
... network, Gaussian process, and support vector regression, to predict mar- ket impact cost accurately and to provide the predictive model that is versatile in the number of ...
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Detecting periodicities with Gaussian processes
... of Gaussian processes, from the combination of one-dimensional periodic kernels to obtain periodic kernels in higher dimension to the use of sparse methods when the number of observation becomes ...for ...
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Degradation modeling for reliability analysis with time-dependent structure based on the inverse gaussian distribution
... inverse Gaussian process intro- duced by Wasan (1968) with some recent papers in the literature, for example, Wang and Xu (2010) proposed an inverse Gaussian process with random effects and ...
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A Monte Carlo Method for the Normal Inverse Gaussian Option Valuation Model using an Inverse Gaussian Bridge
... inverse Gaussian process and its application to option ...Gaussian process. In the third section we show how an inverse Gaussian bridge can be constructed and ...
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PREDICTIVE ANALYTICS VIA GAUSSIAN PROCESSES AND STATISTICAL AUDIT VIA GAUSSIAN MIXTURES IN
... stochastic process schemes for modeling dependent data primarily due two essential properties that dictate the behavior of the predicted variable ...a Gaussian process is completely determined by its ...
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UM MODELO ESPAÇO-TEMPORAL BASEADO EM PROCESSOS GAUSSIANOS PARA PREVISÃO DE INCIDÊNCIA DE DENGUE
... C828s A spatio-temporal gaussian process-based model for forecasting dengue fever incidence.. Dissertação (mestrado) - Universidade Federal de.[r] ...
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João Beleza Teixeira Seixas e Sousa
... sian process, to market observed zero coupon bond log prices, using the Gaussian processes for Machine Learning framework (Rasmussen and Williams ...underlying Gaussian process as an ...
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Mat. Res. vol.6 número2
... Homogeneous Gaussian Profile P + -Type Emitters: Updated Parameters and Metal-Grid Optimization,. by M[r] ...
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GPU-Based De- tection of Protein Cavities using Gaussian Surfaces
... visibility test to retain those that are deemed to be cavity samples. Similarly, Krone et al. [8] use a Gaussian sur- face that better adjusts to SES, in conformity with the parameters set in [20] and [19]. But, ...
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Multi-compartment T2 relaxometry using a spatially constrained multi-Gaussian model.
... Unlike the whole brain coverage we demonstrate, previous T2 relaxometry studies of MS are generally reported on selected slices [33,34], hence preclude the quantification of diffuse or systemic pathologies. Our ...
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Polynomial expansion of the probability density function about gaussian mixtures
... The proposed expansion is based on the Parzen estimation and uses the derivatives of known expansions (Gram-Charlier and Edgeworth) to a sum of Gaussiairs wit,h different[r] ...
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Bayesian Outlier Detection in Non-Gaussian Autoregressive Time Series
... for Gaussian long-memory models, Chan and Cheung (1994) for threshold autoregressive models, Kleiner and Martin (1979) consider robust frequency domain ...of Gaussian linear time ...
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Braz. J. Phys. vol.37 número3A
... the Gaussian fit in the x and z directions respectively: the source image seems to exhibit a non-Gaussian tail which extends beyond the range of the Gaussian fit for r > 17 fm in the out and long ...
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Level density for deformations of the Gaussian orthogonal ensemble
... transition, Gaussian orthogonal random matrix ...about Gaussian ensembles, we derive formulas for the average level density for sid the transition from the Gaussian orthogonal ensemble sGOEd to the ...
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Noise-Robust Speaker Recognition using Reduced Multiconditional Gaussian Mixture Models
... on Gaussian Mixture Models (GMMs) and using Mel Frequency Cepstral Coefficient (MFCC) parameters, have proven to be quite successful at identifying the author of a voice ...
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Image Segmentation by Using Finite Bivariate Doubly Truncated Gaussian Mixture Model
... the process of dividing an image into different regions such that each region is ...on Gaussian mixture models, image segmentation based on Gaussian mixture models has also become very ...through ...
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Robust video coder solution for wireless streaming: applications in Gaussian channels
... The MQ-encoder is ran with the RESTART [26] mode switch enabled, which forces the restart of the MQ-coder at the beginning of each coding pass. Besides the obvious error-resilience provided by this encoding mode, it is ...
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