1. Amestoy, P., et al.: Mixed precision low rank approximations and their application to block low rank LU factorization. IMA J. Numer. Anal. 43(4), 2198–2227 (2023). https://doi.org/10.1093/imanum/drac037
2. Baboulin, M., Kaya, O., Mary, T., Robeyns, M.: Mixed precision iterative refinement for low-rank matrix and tensor approximations (2023). https://inria.hal.science/hal-04115337
3. Blanchard, P., Higham, N.J., Lopez, F., Mary, T., Pranesh, S.: Mixed precision block fused multiply-add: Error analysis and application to GPU tensor cores. SIAM J. Sci. Comput. 42(3), C124–C141 (2020). https://doi.org/10.1137/19M1289546
4. Connolly, M.P., Higham, N.J., Pranesh, S.: Randomized low rank matrix approximation: rounding error analysis and a mixed precision algorithm. MIMS EPrint 2022.5, Manchester Institute for Mathematical Sciences, The University of Manchester, UK (2022). http://eprints.maths.manchester.ac.uk/2863/
5. Fasi, M., Higham, N.J., Lopez, F., Mary, T., Mikaitis, M.: Matrix multiplication in multiword arithmetic: error analysis and application to GPU tensor cores. J-SISC 45(1), C1–C19 (2023). https://doi.org/10.1137/21m1465032