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Likelihood Approximation With Hierarchical Matrices For Large Spatial
  Datasets
v1v2 (latest)

Likelihood Approximation With Hierarchical Matrices For Large Spatial Datasets

8 September 2017
A. Litvinenko
Ying Sun
M. Genton
David E. Keyes
ArXiv (abs)PDFHTML

Papers citing "Likelihood Approximation With Hierarchical Matrices For Large Spatial Datasets"

9 / 9 papers shown
Title
Scalable Physics-based Maximum Likelihood Estimation using Hierarchical
  Matrices
Scalable Physics-based Maximum Likelihood Estimation using Hierarchical Matrices
Yian Chen
M. Anitescu
41
8
0
17 Mar 2023
Scalable3-BO: Big Data meets HPC - A scalable asynchronous parallel
  high-dimensional Bayesian optimization framework on supercomputers
Scalable3-BO: Big Data meets HPC - A scalable asynchronous parallel high-dimensional Bayesian optimization framework on supercomputers
Anh Tran
55
0
0
12 Aug 2021
Identification of unknown parameters and prediction with hierarchical
  matrices
Identification of unknown parameters and prediction with hierarchical matrices
A. Litvinenko
Ronald Kriemann
V. Berikov
18
0
0
14 Apr 2021
Solving weakly supervised regression problem using low-rank manifold
  regularization
Solving weakly supervised regression problem using low-rank manifold regularization
V. Berikov
A. Litvinenko
27
2
0
13 Apr 2021
Geostatistical Modeling and Prediction Using Mixed-Precision Tile
  Cholesky Factorization
Geostatistical Modeling and Prediction Using Mixed-Precision Tile Cholesky Factorization
Sameh Abdulah
Hatem Ltaief
Ying Sun
M. Genton
David E. Keyes
49
20
0
08 Jan 2020
Semi-Supervised Regression using Cluster Ensemble and Low-Rank
  Co-Association Matrix Decomposition under Uncertainties
Semi-Supervised Regression using Cluster Ensemble and Low-Rank Co-Association Matrix Decomposition under Uncertainties
V. Berikov
A. Litvinenko
42
7
0
13 Jan 2019
Scalable Gaussian Process Computations Using Hierarchical Matrices
Scalable Gaussian Process Computations Using Hierarchical Matrices
Christopher J. Geoga
M. Anitescu
Michael L. Stein
84
43
0
09 Aug 2018
Neural-net-induced Gaussian process regression for function
  approximation and PDE solution
Neural-net-induced Gaussian process regression for function approximation and PDE solution
G. Pang
Liu Yang
George Karniadakis
78
73
0
22 Jun 2018
ExaGeoStat: A High Performance Unified Software for Geostatistics on
  Manycore Systems
ExaGeoStat: A High Performance Unified Software for Geostatistics on Manycore Systems
Sameh Abdulah
Hatem Ltaief
Ying Sun
M. Genton
David E. Keyes
92
67
0
09 Aug 2017
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