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Contributed Discussion [A Bayesian Conjugate Gradient Method]

Briol, F-X; DiazDelaO, FA; Hristov, PO; (2019) Contributed Discussion [A Bayesian Conjugate Gradient Method]. Bayesian Analysis , 14 (3) pp. 980-984. 10.1214/19-BA1145. Green open access

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Abstract

We would like to congratulate the authors of "A Bayesian Conjugate Gradient Method" on their insightful paper, and welcome this publication which we firmly believe will become a fundamental contribution to the growing field of probabilistic numerical methods and in particular the sub-field of Bayesian numerical methods. In this short piece, which will be published as a comment alongside the main paper, we first initiate a discussion on the choice of priors for solving linear systems, then propose an extension of the Bayesian conjugate gradient (BayesCG) algorithm for solving several related linear systems simultaneously.

Type: Article
Title: Contributed Discussion [A Bayesian Conjugate Gradient Method]
Open access status: An open access version is available from UCL Discovery
DOI: 10.1214/19-BA1145
Publisher version: https://doi.org/10.1214/19-BA1145
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Mathematics
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Mathematics > Clinical Operational Research Unit
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/10080002
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