Pages that link to "Item:Q2339938"
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The following pages link to Asymptotic analysis of the learning curve for Gaussian process regression (Q2339938):
Displaying 12 items.
- Sequential design strategies for mean response surface metamodeling via stochastic kriging with adaptive exploration and exploitation (Q1683081) (← links)
- Discovering variable fractional orders of advection-dispersion equations from field data using multi-fidelity Bayesian optimization (Q1694642) (← links)
- Learning ``best'' kernels from data in Gaussian process regression. With application to aerodynamics (Q2083686) (← links)
- Physics-informed cokriging: a Gaussian-process-regression-based multifidelity method for data-model convergence (Q2222351) (← links)
- (Q2933867) (← links)
- Asymptotic behaviour in learning from stochastic examples: one-step RSB calculation of the learning curve (Q4227635) (← links)
- Learning Curves for Gaussian Process Regression: Approximations and Bounds (Q4542429) (← links)
- Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models (Q4991044) (← links)
- Learning curves for LMS and regular Gaussian processes (Q5267247) (← links)
- Regularity dependence of the rate of convergence of the learning curve for Gaussian process regression (Q6236263) (← links)
- Bayesian estimation of large-scale simulation models with Gaussian process regression surrogates (Q6573308) (← links)
- Covariance parameter estimation of Gaussian processes with approximated functional inputs (Q6656675) (← links)
