Pages that link to "Item:Q2009833"

The following pages link to Advances in Gaussian random field generation: a review (Q2009833):

Displaying 16 items.

• Quantifying the effect of two-point correlations on the effective elasticity of specific classes of random porous materials with and without connectivity (Q2042334) (← links)
• Fast generation of Gaussian random fields for direct numerical simulations of stochastic transport (Q2058803) (← links)
• Stochastic modeling of inhomogeneities in the aortic wall and uncertainty quantification using a Bayesian encoder-decoder surrogate (Q2096832) (← links)
• Augmented Gaussian random field: theory and computation (Q2129158) (← links)
• Uncertainty quantification of microstructure variability and mechanical behavior of additively manufactured lattice structures (Q2237791) (← links)
• Goal-oriented adaptive finite element multilevel Monte Carlo with convergence rates (Q2679328) (← links)
• Initialization of the circulant embedding method to speed up the generation of Gaussian random fields (Q2679841) (← links)
• A fractional PDE model for turbulent velocity fields near solid walls (Q3389308) (← links)
• Series representations and simulations of isotropic random fields in the Euclidean space (Q5018759) (← links)
• Effective Generation of Compressed Stationary Gaussian Fields (Q5075233) (← links)
• Simple and efficient pseudorandom generators from gaussian processes (Q5091754) (← links)
• Efficient generation of multi-scale random fields: A hierarchical approach (Q5187900) (← links)
• Can cancer cells inform us about the tumor microenvironment? (Q6054220) (← links)
• Meta-auto-decoder: a meta-learning-based reduced order model for solving parametric partial differential equations (Q6575297) (← links)
• Finite elements for Matérn-type random fields: uncertainty in computational mechanics and design optimization (Q6588299) (← links)
• Approximation and generalization of DeepONets for learning operators arising from a class of singularly perturbed problems (Q6630935) (← links)