Review for NeurIPS paper: Probabilistic Linear Solvers for Machine Learning

The paper proposes a new probabilistic solver for linear systems and shows that it can improve uncertainty quantification for linear solvers which is fundamental building block that's widely used in machine learning. This is a well-written paper, I particularly enjoyed Table 1 which helps situate the work in the wider literature. The author rebuttal addresses most of the major concerns and all reviewers lean towards accept in the final discussion.