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1402.4281
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Bayesian and Maximum Likelihood Estimation for Gaussian Processes on an Incomplete Lattice
18 February 2014
Jonathan R. Stroud
Michael L. Stein
Shaun Lysen
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Papers citing
"Bayesian and Maximum Likelihood Estimation for Gaussian Processes on an Incomplete Lattice"
20 / 20 papers shown
The inverse Kalman filter
X. Fang
Mengyang Gu
270
1
0
14 Jul 2024
Iterative Methods for Full-Scale Gaussian Process Approximations for Large Spatial Data
Tim Gyger
Reinhard Furrer
Fabio Sigrist
448
5
0
23 May 2024
Vecchia-approximated Deep Gaussian Processes for Computer Experiments
Journal of Computational And Graphical Statistics (JCGS), 2022
Annie Sauer
A. Cooper
R. Gramacy
358
50
0
06 Apr 2022
Scalable marginalization of correlated latent variables with applications to learning particle interaction kernels
The New England Journal of Statistics in Data Science (JNESDS), 2022
Mengyang Gu
Xubo Liu
X. Fang
Sui Tang
285
8
0
16 Mar 2022
Adapting conditional simulation using circulant embedding for irregularly spaced spatial data
M. Bailey
S. Bandyopadhyay
D. Nychka
195
4
0
22 Sep 2021
Modeling Massive Spatial Datasets Using a Conjugate Bayesian Linear Regression Framework
Spatial Statistics (SS), 2020
Sudipto Banerjee
160
17
0
09 Sep 2021
Learning particle swarming models from data with Gaussian processes
Mathematics of Computation (Math. Comp.), 2021
Jinchao Feng
Charles Kulick
Yunxiang Ren
Sui Tang
451
10
0
04 Jun 2021
Lattice partition recovery with dyadic CART
Neural Information Processing Systems (NeurIPS), 2021
Oscar Hernan Madrid Padilla
Yi Yu
Alessandro Rinaldo
392
6
0
27 May 2021
Identification of unknown parameters and prediction with hierarchical matrices
A. Litvinenko
Ronald Kriemann
V. Berikov
143
0
0
14 Apr 2021
Faster Kernel Interpolation for Gaussian Processes
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Mohit Yadav
Daniel Sheldon
Cameron Musco
BDL
294
13
0
28 Jan 2021
Gaussian orthogonal latent factor processes for large incomplete matrices of correlated data
Bayesian Analysis (BA), 2020
Mengyang Gu
Hanmo Li
192
9
0
21 Nov 2020
Deep Gaussian Markov Random Fields
International Conference on Machine Learning (ICML), 2020
Per Sidén
Fredrik Lindsten
BDL
299
24
0
18 Feb 2020
Gaussian Processes with Errors in Variables: Theory and Computation
Journal of machine learning research (JMLR), 2019
Shuang Zhou
D. Pati
Tianying Wang
Yun Yang
R. Carroll
353
8
0
14 Oct 2019
The Debiased Spatial Whittle Likelihood
Journal of The Royal Statistical Society Series B-statistical Methodology (JRSSB), 2019
Arthur Guillaumin
A. Sykulski
S. Olhede
F. Simons
300
20
0
04 Jul 2019
Prior-preconditioned conjugate gradient method for accelerated Gibbs sampling in "large
n
n
n
& large
p
p
p
" Bayesian sparse regression
A. Nishimura
M. Suchard
529
26
0
29 Oct 2018
Vecchia approximations of Gaussian-process predictions
Matthias Katzfuss
J. Guinness
Wenlong Gong
Daniel Zilber
401
112
0
08 May 2018
HLIBCov: Parallel Hierarchical Matrix Approximation of Large Covariance Matrices and Likelihoods with Applications in Parameter Identification
A. Litvinenko
188
3
0
24 Sep 2017
Likelihood Approximation With Hierarchical Matrices For Large Spatial Datasets
A. Litvinenko
Ying Sun
M. Genton
David E. Keyes
184
54
0
08 Sep 2017
Efficient algorithms for Bayesian Nearest Neighbor Gaussian Processes
Journal of Computational And Graphical Statistics (JCGS), 2017
Andrew O. Finley
A. Datta
B. Cook
Douglas C. Morton
Hans-Erik Andersen
Sudipto Banerjee
419
170
0
01 Feb 2017
Exact Inference for Gaussian Process Regression in case of Big Data with the Cartesian Product Structure
Mikhail Belyaev
Evgeny Burnaev
Yermek Kapushev
TPM
154
20
0
26 Mar 2014
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