Pages that link to "Item:Q1680849"
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The following pages link to Large scale variable fidelity surrogate modeling (Q1680849):
Displaying 16 items.
- Computationally efficient algorithm for Gaussian process regression in case of structured samples (Q327224) (← links)
- Large scale variable fidelity surrogate modeling (Q1680849) (← links)
- Theoretical investigations of the new cokriging method for variable-fidelity surrogate modeling. Well-posedness and maximum likelihood training. (Q1756916) (← links)
- A blackbox yield estimation workflow with Gaussian process regression applied to the design of electromagnetic devices (Q1980858) (← links)
- Systems of Gaussian process models for directed chains of solvers (Q1988026) (← links)
- Locally induced Gaussian processes for large-scale simulation experiments (Q2058747) (← links)
- Stochastic multi-fidelity surrogate modeling of dendritic crystal growth (Q2138818) (← links)
- Enhanced variable-fidelity surrogate-based optimization framework by Gaussian process regression and fuzzy clustering (Q2184447) (← links)
- Robust optimisation of computationally expensive models using adaptive multi-fidelity emulation (Q2240278) (← links)
- Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian processes (Q2246340) (← links)
- Coupling multi-fidelity Kriging and model-order reduction for the construction of virtual charts (Q2281513) (← links)
- Robust additive Gaussian process models using reference priors and cut-off-designs (Q2307104) (← links)
- Surrogate modeling of multiscale models using kernel methods (Q2952618) (← links)
- Bifidelity Surrogate Modelling: Showcasing the Need for New Test Instances (Q5060781) (← links)
- Multifidelity Surrogate Modeling for Time-Series Outputs (Q6164166) (← links)
- Fundamentals of Data-Driven Surrogate Modeling (Q6177991) (← links)
