Results 281 to 290 of about 57,267 (303)
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1998
Recall, a family {ξ} of real valued random variables is called Gaussian if the joint probability distribution of these (taken in finite number) random variables is Gaussian. The Gaussian probability distribution in R n of random variables (ξ 1,..., ξ n ) has the characteristic function $$ Eexp\left\{ {i\sum\limits_{k = 1}^n {{\lambda _k}{\zeta _k}}
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Recall, a family {ξ} of real valued random variables is called Gaussian if the joint probability distribution of these (taken in finite number) random variables is Gaussian. The Gaussian probability distribution in R n of random variables (ξ 1,..., ξ n ) has the characteristic function $$ Eexp\left\{ {i\sum\limits_{k = 1}^n {{\lambda _k}{\zeta _k}}
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Neural Gaussian Conditional Random Fields
2014We propose a Conditional Random Field (CRF) model for structured regression. By constraining the feature functions as quadratic functions of outputs, the model can be conveniently represented in a Gaussian canonical form. We improved the representational power of the resulting Gaussian CRF (GCRF) model by (1) introducing an adaptive feature function ...
Vladan Radosavljevic +2 more
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1994
After some general results relating mixing properties of a Gaussian random field, we propose an explicit bound of the mixing coefficients of such a random field based on the approximation properties of its spectral density in § 2.1.1. In § 2.1.2. more precise results characterize the decay of such coefficients for Gaussian processes. In this chapter, X
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After some general results relating mixing properties of a Gaussian random field, we propose an explicit bound of the mixing coefficients of such a random field based on the approximation properties of its spectral density in § 2.1.1. In § 2.1.2. more precise results characterize the decay of such coefficients for Gaussian processes. In this chapter, X
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Fitting Gaussian Markov Random Fields to Gaussian Fields
Scandinavian Journal of Statistics, 2002Håvard Rue, Hakon Tjelmeland
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Bayesian estimation for homogeneous and inhomogeneous Gaussian random fields
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998Robert G Aykroyd
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Multi-fidelity Gaussian process regression for prediction of random fields
Journal of Computational Physics, 2017Lucia Parussini, D Venturi
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Gaussian Markov Random Fields for Discrete Optimization via Simulation: Framework and Algorithms
Operations Research, 2019Peter Salemi +2 more
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Fast generation of isotropic Gaussian random fields on the sphere
Monte Carlo Methods and Applications, 2018Peter Creasey, Annika Lang
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Approximation of maximum of Gaussian random fields
Journal of Mathematical Analysis and Applications, 2018Enkelejd Hashorva +2 more
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