Contributed Discussion of "A Bayesian Conjugate Gradient Method"
This is an incremental contribution to probabilistic numerical methods, specifically for researchers in Bayesian numerical methods.
The authors discuss and extend a Bayesian conjugate gradient method for solving linear systems, proposing an algorithm for handling multiple related systems simultaneously.
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.