Scaled Vecchia Approximation for Fast Computer-Model Emulation
From MaRDI portal
Publication:5097836
DOI10.1137/20M1352156zbMath1493.62011arXiv2005.00386WikidataQ114074180 ScholiaQ114074180MaRDI QIDQ5097836
Matthias Katzfuss, Earl Lawrence, Joseph Guinness
Publication date: 1 September 2022
Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2005.00386
Gaussian processFisher scoringnearest neighborscomputer experimentsparse inverse Choleskymaximin ordering
Computational methods for problems pertaining to statistics (62-08) Inference from spatial processes (62M30) Applications of statistics in engineering and industry; control charts (62P30)
Related Items
Large-scale local surrogate modeling of stochastic simulation experiments, Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inference, Vecchia-approximated Deep Gaussian Processes for Computer Experiments
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Gaussian Process Learning via Fisher Scoring of Vecchia's Approximation
- Compression, inversion, and approximate PCA of dense kernel matrices at near-linear computational complexity
- Efficient Algorithms for Bayesian Nearest Neighbor Gaussian Processes
- 2010 Rietz lecture: When does the screening effect hold?
- Efficient emulators of computer experiments using compactly supported correlation functions, with an application to cosmology
- Vecchia-Laplace approximations of generalized Gaussian processes for big non-Gaussian spatial data
- Improving the performance of predictive process modeling for large datasets
- Assessing probabilistic forecasts of multivariate quantities, with an application to ensemble predictions of surface winds
- Efficient global optimization of expensive black-box functions
- Interpolation of spatial data. Some theory for kriging
- Design and analysis of computer experiments. With comments and a rejoinder by the authors
- Structured discrepancy in Bayesian model calibration for ChemCam on the Mars Curiosity rover
- A case study competition among methods for analyzing large spatial data
- Nonseparable dynamic nearest neighbor Gaussian process models for large spatio-temporal data with an application to particulate matter analysis
- Bayesian Calibration of Computer Models
- Bayesian Design and Analysis of Computer Experiments: Use of Derivatives in Surface Prediction
- Gaussian Predictive Process Models for Large Spatial Data Sets
- Uncertainty Quantification Using the Nearest Neighbor Gaussian Process
- Combining Field Data and Computer Simulations for Calibration and Prediction
- Approximating Likelihoods for Large Spatial Data Sets
- Fast Prediction of Deterministic Functions Using Sparse Grid Experimental Designs
- A class of multi-resolution approximations for large spatial datasets
- Sparse Cholesky Factorization by Kullback--Leibler Minimization
- Emulating Satellite Drag from Large Simulation Experiments
- A general framework for Vecchia approximations of Gaussian processes