Gaussian Process Learning via Fisher Scoring of Vecchia's Approximation
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Publication:125192
DOI10.48550/arXiv.1905.08374zbMath1475.62033arXiv1905.08374OpenAlexW3134488295MaRDI QIDQ125192
Publication date: 20 May 2019
Published in: Statistics and Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1905.08374
Related Items (11)
A functional-data approach to the Argo data ⋮ Scaled Vecchia Approximation for Fast Computer-Model Emulation ⋮ Scalable semiparametric spatio-temporal regression for large data analysis ⋮ Distributed Bayesian inference in massive spatial data ⋮ Fitting Matérn smoothness parameters using automatic differentiation ⋮ Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inference ⋮ Scalable computations for nonstationary Gaussian processes ⋮ Vecchia-approximated Deep Gaussian Processes for Computer Experiments ⋮ GpGp ⋮ Hierarchical Bayesian modeling of ocean heat content and its uncertainty ⋮ Discussion on competition on spatial statistics for large datasets
Cites Work
- Scalable Gaussian Process Computations Using Hierarchical Matrices
- Approximating Likelihoods for Large Spatial Data Sets
- Inconsistent Estimation and Asymptotically Equal Interpolations in Model-Based Geostatistics
- A Simplex Method for Function Minimization
- A general framework for Vecchia approximations of Gaussian processes
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