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A multi-resolution approximation for massive spatial datasets
v1v2 (latest)

A multi-resolution approximation for massive spatial datasets

16 July 2015
Matthias Katzfuss
ArXiv (abs)PDFHTML

Papers citing "A multi-resolution approximation for massive spatial datasets"

42 / 42 papers shown
Title
Bayesian Data Sketching for Varying Coefficient Regression Models
Bayesian Data Sketching for Varying Coefficient Regression Models
Rajarshi Guhaniyogi
Laura Baracaldo
Sudipto Banerjee
28
5
0
30 May 2025
Iterative Methods for Full-Scale Gaussian Process Approximations for Large Spatial Data
Iterative Methods for Full-Scale Gaussian Process Approximations for Large Spatial Data
Tim Gyger
Reinhard Furrer
Fabio Sigrist
65
2
0
23 May 2024
Normalizing Basis Functions: Approximate Stationary Models for Large
  Spatial Data
Normalizing Basis Functions: Approximate Stationary Models for Large Spatial Data
Antony Sikorski
Daniel McKenzie
Douglas Nychka
217
3
0
22 May 2024
Logistic-beta processes for dependent random probabilities with beta marginals
Logistic-beta processes for dependent random probabilities with beta marginals
Changwoo J. Lee
Alessandro Zito
Huiyan Sang
David B. Dunson
79
0
0
10 Feb 2024
Numerically Stable Sparse Gaussian Processes via Minimum Separation
  using Cover Trees
Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees
Alexander Terenin
David R. Burt
A. Artemev
Seth Flaxman
Mark van der Wilk
C. Rasmussen
Hong Ge
99
7
0
14 Oct 2022
Kernel Packet: An Exact and Scalable Algorithm for Gaussian Process
  Regression with Matérn Correlations
Kernel Packet: An Exact and Scalable Algorithm for Gaussian Process Regression with Matérn Correlations
Hao Chen
Liang Ding
Rui Tuo
38
12
0
07 Mar 2022
Multi-model Ensemble Analysis with Neural Network Gaussian Processes
Multi-model Ensemble Analysis with Neural Network Gaussian Processes
Trevor Harris
Yangqiu Song
Ryan Sriver
113
5
0
08 Feb 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
Correlation-based sparse inverse Cholesky factorization for fast
  Gaussian-process inference
Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inference
Myeong K. Kang
Matthias Katzfuss
72
24
0
29 Dec 2021
Modeling Massive Spatial Datasets Using a Conjugate Bayesian Linear
  Regression Framework
Modeling Massive Spatial Datasets Using a Conjugate Bayesian Linear Regression Framework
Sudipto Banerjee
49
13
0
09 Sep 2021
D-STEM v2: A Software for Modelling Functional Spatio-Temporal Data
D-STEM v2: A Software for Modelling Functional Spatio-Temporal Data
Yaqiong Wang
F. Finazzi
A. Fassò
11
6
0
27 Jan 2021
Kryging: Geostatistical analysis of large-scale datasets using Krylov
  subspace methods
Kryging: Geostatistical analysis of large-scale datasets using Krylov subspace methods
Suman Majumder
Yawen Guan
Brian J. Reich
A. Saibaba
35
4
0
24 Dec 2020
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
Unifying Compactly Supported and Matern Covariance Functions in Spatial
  Statistics
Unifying Compactly Supported and Matern Covariance Functions in Spatial Statistics
M. Bevilacqua
Christian Caamaño-Carrillo
Emilio Porcu
54
30
0
06 Aug 2020
Hierarchical sparse Cholesky decomposition with applications to
  high-dimensional spatio-temporal filtering
Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering
M. Jurek
Matthias Katzfuss
48
20
0
30 Jun 2020
Spatiotemporal Multi-Resolution Approximations for Analyzing Global
  Environmental Data
Spatiotemporal Multi-Resolution Approximations for Analyzing Global Environmental Data
M. Appel
E. Pebesma
41
13
0
30 Jun 2020
Spatial Factor Modeling: A Bayesian Matrix-Normal Approach for
  Misaligned Data
Spatial Factor Modeling: A Bayesian Matrix-Normal Approach for Misaligned Data
Lu Zhang
Sudipto Banerjee
37
27
0
31 May 2020
Precision Aggregated Local Models
Precision Aggregated Local Models
Adam Edwards
R. Gramacy
13
8
0
27 May 2020
Additive stacking for disaggregate electricity demand forecasting
Additive stacking for disaggregate electricity demand forecasting
Christian Capezza
B. Palumbo
Y. Goude
S. Wood
Matteo Fasiolo
AI4TS
85
7
0
20 May 2020
Scaled Vecchia approximation for fast computer-model emulation
Scaled Vecchia approximation for fast computer-model emulation
Matthias Katzfuss
J. Guinness
E. Lawrence
53
40
0
01 May 2020
Sparse Cholesky factorization by Kullback-Leibler minimization
Sparse Cholesky factorization by Kullback-Leibler minimization
Florian Schäfer
Matthias Katzfuss
H. Owhadi
102
95
0
29 Apr 2020
Hierarchical Bayesian Nearest Neighbor Co-Kriging Gaussian Process
  Models; An Application to Intersatellite Calibration
Hierarchical Bayesian Nearest Neighbor Co-Kriging Gaussian Process Models; An Application to Intersatellite Calibration
Sibo Cheng
B. Konomi
J. Matthews
G. Karagiannis
E. Kang
SyDa
32
7
0
03 Apr 2020
Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian
  Processes on Partitioned Domains
Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian Processes on Partitioned Domains
M. Peruzzi
Sudipto Banerjee
Andrew O. Finley
74
55
0
25 Mar 2020
Deep Gaussian Markov Random Fields
Deep Gaussian Markov Random Fields
Per Sidén
Fredrik Lindsten
BDL
57
22
0
18 Feb 2020
spNNGP R package for Nearest Neighbor Gaussian Process models
spNNGP R package for Nearest Neighbor Gaussian Process models
Andrew O. Finley
A. Datta
S. Banerjee
30
27
0
24 Jan 2020
Large-scale inference of correlation among mixed-type biological traits
  with phylogenetic multivariate probit models
Large-scale inference of correlation among mixed-type biological traits with phylogenetic multivariate probit models
Zhenyu Zhang
A. Nishimura
P. Bastide
X. Ji
R. Payne
P. Goulder
P. Lemey
M. Suchard
42
29
0
19 Dec 2019
Max-and-Smooth: a two-step approach for approximate Bayesian inference
  in latent Gaussian models
Max-and-Smooth: a two-step approach for approximate Bayesian inference in latent Gaussian models
B. Hrafnkelsson
S. Siegert
Raphael Huser
H. Bakka
Árni V. Jóhannesson
71
18
0
27 Jul 2019
Multi-Scale Process Modelling and Distributed Computation for Spatial
  Data
Multi-Scale Process Modelling and Distributed Computation for Spatial Data
A. Zammit‐Mangion
J. Rougier
259
11
0
17 Jul 2019
The Debiased Spatial Whittle Likelihood
The Debiased Spatial Whittle Likelihood
Arthur Guillaumin
A. Sykulski
S. Olhede
F. Simons
12
11
0
04 Jul 2019
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
Pushing the Limit: A Hybrid Parallel Implementation of the
  Multi-resolution Approximation for Massive Data
Pushing the Limit: A Hybrid Parallel Implementation of the Multi-resolution Approximation for Massive Data
Huang Huang
Lewis R. Blake
D. Hammerling
22
8
0
30 Apr 2019
Multi-resolution filters for massive spatio-temporal data
Multi-resolution filters for massive spatio-temporal data
M. Jurek
Matthias Katzfuss
58
24
0
09 Oct 2018
Scalable Gaussian Process Computations Using Hierarchical Matrices
Scalable Gaussian Process Computations Using Hierarchical Matrices
Christopher J. Geoga
M. Anitescu
Michael L. Stein
74
43
0
09 Aug 2018
Scalable Gaussian Process Inference with Finite-data Mean and Variance
  Guarantees
Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees
Jonathan H. Huggins
Trevor Campbell
Mikolaj Kasprzak
Tamara Broderick
76
15
0
26 Jun 2018
Vecchia approximations of Gaussian-process predictions
Vecchia approximations of Gaussian-process predictions
Matthias Katzfuss
J. Guinness
Wenlong Gong
Daniel Zilber
95
93
0
08 May 2018
Spatial Mapping with Gaussian Processes and Nonstationary Fourier
  Features
Spatial Mapping with Gaussian Processes and Nonstationary Fourier Features
Jean-François Ton
Seth Flaxman
Dino Sejdinovic
Samir Bhatt
GP
73
55
0
15 Nov 2017
Spatial Statistical Downscaling for Constructing High-Resolution Nature
  Runs in Global Observing System Simulation Experiments
Spatial Statistical Downscaling for Constructing High-Resolution Nature Runs in Global Observing System Simulation Experiments
P. Ma
E. Kang
A. Braverman
H. Nguyen
AI4Cl
18
10
0
01 Nov 2017
A class of multi-resolution approximations for large spatial datasets
A class of multi-resolution approximations for large spatial datasets
Matthias Katzfuss
Wenlong Gong
GP
168
30
0
24 Oct 2017
A general framework for Vecchia approximations of Gaussian processes
A general framework for Vecchia approximations of Gaussian processes
Matthias Katzfuss
J. Guinness
95
262
0
21 Aug 2017
A sparse linear algebra algorithm for fast computation of prediction
  variances with Gaussian Markov random fields
A sparse linear algebra algorithm for fast computation of prediction variances with Gaussian Markov random fields
A. Zammit‐Mangion
J. Rougier
51
7
0
04 Jul 2017
Efficient algorithms for Bayesian Nearest Neighbor Gaussian Processes
Efficient algorithms for Bayesian Nearest Neighbor Gaussian Processes
Andrew O. Finley
A. Datta
B. Cook
Douglas C. Morton
Hans-Erik Andersen
Sudipto Banerjee
149
156
0
01 Feb 2017
Parallel inference for massive distributed spatial data using low-rank
  models
Parallel inference for massive distributed spatial data using low-rank models
Matthias Katzfuss
D. Hammerling
134
34
0
06 Feb 2014
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