This Mathematica notebook accompanies the paper "Local, algebraic simplifications of Gaussian random fields" by Theodor Bjorkmo and M. C. David Marsh. It can be used to 1) generate Gaussian random fields (with a square exponential covariance function) through a local Taylor expansion; 2) constrain the hyperparameters of the covariance function given training data in the form of such Taylor coefficients. The script is commented throughout
International audienceThe Circulant Embedding Method (CEM) is a well known technique to generate sta...
Abstract. Fast Fourier transforms are used to develop algorithms for the fast generation of correlat...
International audienceA general method to generate simulated paths of non-Gaussian homogeneous rando...
Natural permeability fields are classically modeled by a second-order stationary field which is a lo...
Random fields are families of random variables, indexed by a d-dimensional parameter x with d> 1....
GaussianRandomFields.jl is a Julia package to compute and sample from Gaussian random fields
The numerical discretization of problems with stochastic data or stochastic parameters generally inv...
International audienceTwo algorithms are proposed to simulate space-time Gaussian random fields with...
ABSTRACT: This work is concerned with the construction of a random generator for non-Gaussian tensor...
This paper presents an algorithm for simulating Gaussian random fields with zero mean and non-statio...
An approach to computational problems associated with generation and estimation of large Gaussian fi...
The efficient simulation of isotropic Gaussian random fields on the unit sphere is a task encountere...
The high-dimensionality typically associated with discretized approximations to Gaussian random fiel...
This thesis is a study on the implementation of the Gaussian Markov Random Field (GMRF) for random s...
Artículo de publicación ISIThis work pertains to the simulation of an intrinsic random field of orde...
International audienceThe Circulant Embedding Method (CEM) is a well known technique to generate sta...
Abstract. Fast Fourier transforms are used to develop algorithms for the fast generation of correlat...
International audienceA general method to generate simulated paths of non-Gaussian homogeneous rando...
Natural permeability fields are classically modeled by a second-order stationary field which is a lo...
Random fields are families of random variables, indexed by a d-dimensional parameter x with d> 1....
GaussianRandomFields.jl is a Julia package to compute and sample from Gaussian random fields
The numerical discretization of problems with stochastic data or stochastic parameters generally inv...
International audienceTwo algorithms are proposed to simulate space-time Gaussian random fields with...
ABSTRACT: This work is concerned with the construction of a random generator for non-Gaussian tensor...
This paper presents an algorithm for simulating Gaussian random fields with zero mean and non-statio...
An approach to computational problems associated with generation and estimation of large Gaussian fi...
The efficient simulation of isotropic Gaussian random fields on the unit sphere is a task encountere...
The high-dimensionality typically associated with discretized approximations to Gaussian random fiel...
This thesis is a study on the implementation of the Gaussian Markov Random Field (GMRF) for random s...
Artículo de publicación ISIThis work pertains to the simulation of an intrinsic random field of orde...
International audienceThe Circulant Embedding Method (CEM) is a well known technique to generate sta...
Abstract. Fast Fourier transforms are used to develop algorithms for the fast generation of correlat...
International audienceA general method to generate simulated paths of non-Gaussian homogeneous rando...