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Hierarchical sparse Cholesky decomposition with applications to
  high-dimensional spatio-temporal filtering
v1v2 (latest)

Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering

30 June 2020
M. Jurek
Matthias Katzfuss
ArXiv (abs)PDFHTML

Papers citing "Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering"

6 / 6 papers shown
Title
Learning non-Gaussian spatial distributions via Bayesian transport maps with parametric shrinkage
Learning non-Gaussian spatial distributions via Bayesian transport maps with parametric shrinkage
Anirban Chakraborty
Matthias Katzfuss
OT
109
1
0
28 Sep 2024
Scalable Model-Based Gaussian Process Clustering
Scalable Model-Based Gaussian Process Clustering
Anirban Chakraborty
Abhisek Chakraborty
50
1
0
14 Sep 2023
Scalable Spatio-Temporal Smoothing via Hierarchical Sparse Cholesky
  Decomposition
Scalable Spatio-Temporal Smoothing via Hierarchical Sparse Cholesky Decomposition
M. Jurek
Matthias Katzfuss
53
9
0
19 Jul 2022
Spatial meshing for general Bayesian multivariate models
Spatial meshing for general Bayesian multivariate models
M. Peruzzi
David B. Dunson
121
7
0
25 Jan 2022
Spatial Multivariate Trees for Big Data Bayesian Regression
Spatial Multivariate Trees for Big Data Bayesian Regression
M. Peruzzi
David B. Dunson
48
10
0
02 Dec 2020
Vecchia-Laplace approximations of generalized Gaussian processes for big
  non-Gaussian spatial data
Vecchia-Laplace approximations of generalized Gaussian processes for big non-Gaussian spatial data
Daniel Zilber
Matthias Katzfuss
84
34
0
18 Jun 2019
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