Pages that link to "Item:Q2894757"
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The following pages link to Gaussian process emulators for the stochastic finite element method (Q2894757):
Displaying 19 items.
- Explicit solution for linear systems with parametric stiffness and application to uncertain structures (Q310549) (← links)
- A hybrid spectral and metamodeling approach for the stochastic finite element analysis of structural dynamic systems (Q460849) (← links)
- A generalized uncertainty propagation criterion from benchmark studies of microstructured material systems (Q465747) (← links)
- Gaussian process emulation for second-order Monte Carlo simulations (Q629122) (← links)
- ANOVA Gaussian process modeling for high-dimensional stochastic computational models (Q781984) (← links)
- A new class of high-order methods for fluid dynamics simulations using Gaussian process modeling: one-dimensional case (Q1668731) (← links)
- The effect of the nugget on Gaussian process emulators of computer models (Q1927203) (← links)
- Emulating dynamic non-linear simulators using Gaussian processes (Q2002727) (← links)
- An efficient dimension reduction for the Gaussian process emulation of two nested codes with functional outputs (Q2203403) (← links)
- The role of surrogate models in the development of digital twins of dynamic systems (Q2241783) (← links)
- Multivariate function approximations using the D-MORPH algorithm (Q2285865) (← links)
- Full-field order-reduced Gaussian process emulators for nonlinear probabilistic mechanics (Q2683438) (← links)
- Deep physics corrector: a physics enhanced deep learning architecture for solving stochastic differential equations (Q2687567) (← links)
- An adaptive Gaussian process emulator for partial differential equations with stochastic parameters (Q3306911) (← links)
- INFERENCE AND UNCERTAINTY PROPAGATION OF ATOMISTICALLY INFORMED CONTINUUM CONSTITUTIVE LAWS, PART 2: GENERALIZED CONTINUUM MODELS BASED ON GAUSSIAN PROCESSES (Q5045421) (← links)
- Comparison of Surrogate-Based Uncertainty Quantification Methods for Computationally Expensive Simulators (Q5269870) (← links)
- Analytical uncertainty quantification approach based on adaptive generalized <scp>co‐Gaussian</scp> process model (Q6092235) (← links)
- Latent variable Gaussian process models: a rank-based analysis and an alternative approach (Q6555541) (← links)
- An efficient metamodeling approach for uncertainty quantification of complex systems with arbitrary parameter probability distributions (Q6565211) (← links)
