Sparse Cholesky factorization by Kullback-Leibler minimization

29 April 2020

Papers citing "Sparse Cholesky factorization by Kullback-Leibler minimization"

17 / 17 papers shown

Title
Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis Yasamin Jalalian Juan Felipe Osorio Ramirez Alexander W. Hsu Bamdad Hosseini H. Owhadi 46 0 0 02 Mar 2025
Learning non-Gaussian spatial distributions via Bayesian transport maps with parametric shrinkage Anirban Chakraborty Matthias Katzfuss OT 26 1 0 28 Sep 2024
Computational Hypergraph Discovery, a Gaussian Process framework for connecting the dots Théo Bourdais Pau Batlle Xianjin Yang Ricardo Baptista Nicolas Rouquette H. Owhadi 21 0 0 28 Nov 2023
Error Analysis of Kernel/GP Methods for Nonlinear and Parametric PDEs Pau Batlle Yifan Chen Bamdad Hosseini H. Owhadi Andrew M. Stuart 34 17 0 08 May 2023
Gaussian Process Hydrodynamics H. Owhadi 24 1 0 21 Sep 2022
Scalable Spatio-Temporal Smoothing via Hierarchical Sparse Cholesky Decomposition M. Jurek Matthias Katzfuss 14 9 0 19 Jul 2022
Variational Bayesian inference for CP tensor completion with side information S. Budzinskiy N. Zamarashkin 13 1 0 24 Jun 2022
Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes Felix Jimenez Matthias Katzfuss 18 10 0 02 Mar 2022
Ordered conditional approximation of Potts models Anirban Chakraborty Matthias Katzfuss J. Guinness TPM 13 1 0 13 Oct 2021
Finite Element Representations of Gaussian Processes: Balancing Numerical and Statistical Accuracy D. Sanz-Alonso Ruiyi Yang 18 12 0 06 Sep 2021
Learning Partial Differential Equations in Reproducing Kernel Hilbert Spaces George Stepaniants 49 15 0 26 Aug 2021
Learning particle swarming models from data with Gaussian processes Jinchao Feng Charles Kulick Yunxiang Ren Sui Tang 26 5 0 04 Jun 2021
Scalable Bayesian computation for crossed and nested hierarchical models O. Papaspiliopoulos Timothée Stumpf-Fétizon Giacomo Zanella 37 10 0 19 Mar 2021
Bayesian nonstationary and nonparametric covariance estimation for large spatial data Brian Kidd Matthias Katzfuss 9 14 0 10 Dec 2020
Unifying Compactly Supported and Matern Covariance Functions in Spatial Statistics M. Bevilacqua Christian Caamaño-Carrillo Emilio Porcu 14 27 0 06 Aug 2020
Scaled Vecchia approximation for fast computer-model emulation Matthias Katzfuss J. Guinness E. Lawrence 14 40 0 01 May 2020
Vecchia-Laplace approximations of generalized Gaussian processes for big non-Gaussian spatial data Daniel Zilber Matthias Katzfuss 19 34 0 18 Jun 2019