Scalable Physics-based Maximum Likelihood Estimation using Hierarchical Matrices

17 March 2023

Papers citing "Scalable Physics-based Maximum Likelihood Estimation using Hierarchical Matrices"

7 / 7 papers shown

Title
Scalable Gaussian Process Computations Using Hierarchical Matrices Christopher J. Geoga M. Anitescu Michael L. Stein 40 42 0 09 Aug 2018
Likelihood Approximation With Hierarchical Matrices For Large Spatial Datasets A. Litvinenko Ying Sun M. Genton David E. Keyes 32 52 0 08 Sep 2017
Multi-Level Restricted Maximum Likelihood Covariance Estimation and Kriging for Large Non-Gridded Spatial Datasets J. Castrillón-Candás M. Genton Rio Yokota 25 22 0 01 Apr 2015
Fast symmetric factorization of hierarchical matrices with applications Sivaram Ambikasaran M. O’Neil Karan Raj Singh 80 26 0 01 May 2014
Fast Direct Methods for Gaussian Processes Sivaram Ambikasaran D. Foreman-Mackey L. Greengard D. Hogg M. O’Neil 77 383 0 24 Mar 2014
A computational framework for infinite-dimensional Bayesian inverse problems. Part I: The linearized case, with application to global seismic inversion T. Bui-Thanh Omar Ghattas James Martin G. Stadler 56 390 0 06 Aug 2013
Optimal Estimation and Rank Detection for Sparse Spiked Covariance Matrices Tony Cai Zongming Ma Yihong Wu 92 160 0 14 May 2013