Gaussian random field
Latin Hypercube Sampling of Gaussian random field for Sobol' global sensitivity analysis of models with spatial inputs and scalar output
... Keywords: global sensitivity analysis; Latin Hypercube Sampling; Gaussian random field; unconditionnal simulation I. I NTRODUCTION Sensitivity analysis (SA) techniques are increasingly recognized as ...
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On ANOVA decompositions of kernels and Gaussian random field paths
... and Gaussian random field paths ...on random field models have been proposed to alleviate these costs, where f is substituted by a (kriging) predictor or by conditional ...of ...
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On ANOVA Decompositions of Kernels and Gaussian Random Field Paths
... of Gaussian random field ...centred Gaussian random fields with independent FANOVA effects, to make progress towards the distribution of Sobol’ indices of Gaussian random ...
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Algorithms for stationary Gaussian random field generation
... Algorithms for stationary Gaussian random field generation 4 1.3 Covariance matrix We discretize Ω over a regular grid composed of N Ω + 1 equally spaced points. Let us considered the discrete ...
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Representations of Gaussian random fields and approximation of elliptic PDEs with lognormal coefficients *
... The periodic continuation has some parallels to circulant embedding, proposed inde- pendently in [14] and [28] as an algebraic technique for evaluating a stationary Gaussian random field, given by ...
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Invariances of random fields paths, with applications in Gaussian Process Regression
... 2], random field models for prediction have become a main stream topic in machine learning (under the Gaussian Process Regression terminology, see, ...a Gaussian random field ...
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Analysis of continuous spectral method for sampling stationary Gaussian random fields
... the length of the domain The main framework of the present paper is to provide an optimal error bounds of the continuous spectral representation method which does not involves any kind of matrix decomposition [5, 17, ...
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Additivity and Ortho-Additivity in Gaussian Random Fields
... with Gaussian random field (GRF) models and their use in functional ...to Gaussian random fields with paths that are orthogonal to the space of additive ...of Gaussian process ...
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On degeneracy and invariances of random fields paths with applications in Gaussian process modelling
... a Gaussian random field model is assumed for some function f of interest, and so all prior assumptions on f are accounted for by the corre- sponding mean function m and covariance kernel ...curl-free ...
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GENFIELD: A parallel software for the generation of stationary Gaussian random fields
... 2. Generate a vector 𝜽 = (𝜃 0 , … , 𝜃 𝑁 ) 𝑇 as a realization of uncorrelated random normal variables with zero mean. 3. One realization is obtained by 𝒀 = 𝑩𝜽. The usual method to decompose 𝑹 is Cholesky. Its cost ...
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Frame-based Gaussian beam shooting from experimental far field data
... The “spectral partitioning” algorithm has been shown to efficiently complement the usual frame- based Gaussian beam shooting method, in the case of non directive antenna fields. The method has been applied to ...
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Markov Random Field for combined defogging and stereo reconstruction
... Visual effect of fog • Color Fades • Airlight added • Contrast and visibility decrease with distance Visibility distance : 250m ⇒ Difficulties for object detection/recognition/identifica[r] ...
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Transformation Methods for Static Field Problems With Random Domains
... using random variables is used in order to take into account these uncertainties ...one random mapping that transforms the random domain into a deterministic ...
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Solution of Static Field Problems With Random Domains
... of random domains compared to the case of random behavior law is that, a priori, geometric variation leads to a modification of the ...are random so does the position of the nodes located on that ...
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Two properties of vectors of quadratic forms in Gaussian random variables
... Keywords: Quadratic forms; second Wiener chaos; convergence in law; absolute continuity. 2000 Mathematics Subject Classification: 60F05; 60G15; 60H05. 1. Introduction and main results Due to many applications in ...
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Comparison and anti-concentration bounds for maxima of Gaussian random vectors
... the Gaussian random vector, which does not hold in our targeted applications in high-dimensional statistics, for example, analysis of Danzig ...the Gaussian random vector, then the upper bound ...
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Markov Random Field Model for Single Image Defogging
... We evaluate the proposed algorithm on 66 synthetic im- ages with uniform fog from the database named FRIDA2 1 . This database was introduced first in [1] and contains a ground-truth for defogging methods. The proposed ...
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Tree Crown Extraction using a Three State Markov Random Field
... Unité de recherche INRIA Sophia Antipolis 2004, route des Lucioles - BP 93 - 06902 Sophia Antipolis Cedex France Unité de recherche INRIA Futurs : Parc Club Orsay Université - ZAC des Vi[r] ...
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Data assimilation with Gaussian mixture models using the dynamically orthogonal field equations
... Adopting techniques prevalent in Machine Learning and Pattern Recognition, and building on the foundations of classical assimilation schemes, we introduce the GMM-DO [r] ...
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Game on Random Environement, Mean-field Langevin System and Neural Networks
... prove the (non-exponential) ergodicity of the MFL system under quite mild conditions on the coefficients. In view of applications, our result can be used to justify the applicability of the gradient descent algorithm ...
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