Statistical properties of BayesCG under the Krylov prior
Reid, T. W., Ipsen, I. C. F., Cockayne, J., & Oates, C. J. (2023, October 12). NUMERISCHE MATHEMATIK.
TL;DR:
Numerical experiments confirm that, under low-rank approximate Krylov posteriors, BayesCG is only slightly optimistic and exhibits the characteristics of a calibrated solver, and is computationally competitive with CG.
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