Pages that link to "Item:Q2058747"
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The following pages link to Locally induced Gaussian processes for large-scale simulation experiments (Q2058747):
Displaying 11 items.
- Vecchia-approximated Deep Gaussian Processes for Computer Experiments (Q84900) (← links)
- Computationally efficient algorithm for Gaussian process regression in case of structured samples (Q327224) (← links)
- Large scale variable fidelity surrogate modeling (Q1680849) (← links)
- Batch-sequential design and heteroskedastic surrogate modeling for delta smelt conservation (Q2154181) (← links)
- Large-scale local surrogate modeling of stochastic simulation experiments (Q2157538) (← links)
- Real-Time Local GP Model Learning (Q3568618) (← links)
- Exploiting Variance Reduction Potential in Local Gaussian Process Search (Q4639563) (← links)
- Sensitivity Prewarping for Local Surrogate Modeling (Q6631098) (← links)
- Active Learning for Deep Gaussian Process Surrogates (Q6631105) (← links)
- A Global-Local Approximation Framework for Large-Scale Gaussian Process Modeling (Q6631207) (← links)
- Augmenting a Simulation Campaign for Hybrid Computer Model and Field Data Experiments (Q6637490) (← links)
