Pages that link to "Item:Q6622448"
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The following pages link to Permutation and Grouping Methods for Sharpening Gaussian Process Approximations (Q6622448):
Displaying 16 items.
- Nearest neighbors weighted composite likelihood based on pairs for (non-)Gaussian massive spatial data with an application to Tukey-\(hh\) random fields estimation (Q6554236) (← links)
- An adaptive factorized Nyström preconditioner for regularized kernel matrices (Q6575352) (← links)
- The Matérn model: a journey through statistics, numerical analysis and machine learning (Q6579154) (← links)
- Extending the generalized Wendland covariance model (Q6595780) (← links)
- Nearest-neighbor sparse Cholesky matrices in spatial statistics (Q6602373) (← links)
- Fixed-domain asymptotics under Vecchia's approximation of spatial process likelihoods (Q6621340) (← links)
- Computationally efficient nonstationary nearest-neighbor Gaussian process models using data-driven techniques (Q6626105) (← links)
- High-dimensional multivariate geostatistics: a Bayesian matrix-normal approach (Q6626391) (← links)
- Conjugate sparse plus low rank models for efficient Bayesian interpolation of large spatial data (Q6626522) (← links)
- Estimating atmospheric motion winds from satellite image data using space-time drift models (Q6626624) (← links)
- Multivariate nearest-neighbors Gaussian processes with random covariance matrices (Q6626655) (← links)
- Recursive nearest neighbor co-kriging models for big multi-fidelity spatial data sets (Q6626668) (← links)
- Sensitivity Prewarping for Local Surrogate Modeling (Q6631098) (← links)
- Bayesian nonparametric generative modeling of large multivariate non-Gaussian spatial fields (Q6655987) (← links)
- The third competition on spatial statistics for large datasets (Q6655988) (← links)
- Implementation and analysis of GPU algorithms for Vecchia approximation (Q6657815) (← links)
