Pages that link to "Item:Q2903301"
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The following pages link to Kernels for vector-valued functions: a review (Q2903301):
Displaying 28 items.
- (Q5214237) (← links)
- On Learning Vector-Valued Functions (Q5696487) (← links)
- Surrogate Modeling with Gaussian Processes for an Inverse Problem in Polymer Dynamics (Q6048312) (← links)
- Deep Gaussian process for multi-objective Bayesian optimization (Q6050375) (← links)
- Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics (Q6053801) (← links)
- Intercorrelated random fields with bounds and the Bayesian identification of their parameters: Application to linear elastic struts and fibers (Q6070085) (← links)
- Structured learning of rigid‐body dynamics: A survey and unified view from a robotics perspective (Q6089645) (← links)
- Large scale multi-output multi-class classification using Gaussian processes (Q6106450) (← links)
- On Negative Transfer and Structure of Latent Functions in Multioutput Gaussian Processes (Q6109146) (← links)
- Gaussian process hydrodynamics (Q6132295) (← links)
- Learning system parameters from Turing patterns (Q6134365) (← links)
- A Bayesian decision framework for optimizing sequential combination antiretroviral therapy in people with HIV (Q6138619) (← links)
- Kernel methods are competitive for operator learning (Q6202132) (← links)
- Learning nonparametric ordinary differential equations from noisy data (Q6553789) (← links)
- Interpolation with uncoupled separable matrix-valued kernels (Q6557260) (← links)
- Bayesian estimation of large-scale simulation models with Gaussian process regression surrogates (Q6573308) (← links)
- Gaussian processes for Bayesian inverse problems associated with linear partial differential equations (Q6581676) (← links)
- Uncertainty modeling and propagation for groundwater flow: a comparative study of surrogates (Q6587664) (← links)
- Heteroscedastic Gaussian process regression for material structure-property relationship modeling (Q6609835) (← links)
- Nonparametric Modeling and Prognosis of Condition Monitoring Signals Using Multivariate Gaussian Convolution Processes (Q6622455) (← links)
- A review on statistical and machine learning competing risks methods (Q6625438) (← links)
- Gaussian kernel with correlated variables for incomplete data (Q6638888) (← links)
- Bayesian optimisation for constrained problems (Q6639392) (← links)
- GFN: a graph feedforward network for resolution-invariant reduced operator learning in multifidelity applications (Q6643617) (← links)
- Gradient-enhanced deep Gaussian processes for multifidelity modeling (Q6648379) (← links)
- From kernel methods to neural networks: a unifying variational formulation (Q6659493) (← links)
- Operator learning with Gaussian processes (Q6669069) (← links)
- Targeted adaptive design (Q6669402) (← links)
