Pages that link to "Item:Q5243733"
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The following pages link to Smoothed Full-Scale Approximation of Gaussian Process Models for Computation of Large Spatial Datasets (Q5243733):
Displaying 17 items.
- A multi-resolution approximation via linear projection for large spatial datasets (Q825323) (← links)
- Vecchia-Laplace approximations of generalized Gaussian processes for big non-Gaussian spatial data (Q830598) (← links)
- Stochastic local interaction model: an alternative to kriging for massive datasets (Q2066859) (← links)
- Kryging: geostatistical analysis of large-scale datasets using Krylov subspace methods (Q2080350) (← links)
- A case study competition among methods for analyzing large spatial data (Q2272997) (← links)
- Efficient computation of Gaussian process regression for large spatial data sets by patching local Gaussian processes (Q2834511) (← links)
- Gaussian process modeling of large-scale terrain (Q2899388) (← links)
- Full-Scale Approximations of Spatio-Temporal Covariance Models for Large Datasets (Q3195190) (← links)
- A class of multi-resolution approximations for large spatial datasets (Q4986350) (← links)
- Large spatial data modeling and analysis: A Krylov subspace approach (Q5043794) (← links)
- Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian Processes on Partitioned Domains (Q5885120) (← links)
- A general framework for Vecchia approximations of Gaussian processes (Q6032766) (← links)
- Scalable computations for nonstationary Gaussian processes (Q6173565) (← links)
- Conjugate sparse plus low rank models for efficient Bayesian interpolation of large spatial data (Q6626522) (← links)
- A Subsampling Method for Regression Problems Based on Minimum Energy Criterion (Q6631125) (← links)
- A Nonstationary Soft Partitioned Gaussian Process Model via Random Spanning Trees (Q6631709) (← links)
- The third competition on spatial statistics for large datasets (Q6655988) (← links)
