Article

Daužickaitė, I. ORCID: https://orcid.org/0000-0002-1285-1764, Lawless, A. S., Scott, J. A. ORCID: https://orcid.org/0000-0003-2130-1091 and Van Leeuwen, P. J. ORCID: https://orcid.org/0000-0003-2325-5340 (2021) Randomised preconditioning for the forcing formulation of weak constraint 4D‐Var. Quarterly Journal of the Royal Meteorological Society. ISSN 1477-870X doi: https://doi.org/10.1002/qj.4151 (In Press)

Dauzickaite, I., Lawless, A. S., Scott, J. A. ORCID: https://orcid.org/0000-0003-2130-1091 and Leeuwen, P. J. (2021) On time-parallel preconditioning for the state formulation of incremental weak constraint 4D-Var. Quarterly Journal of the Royal Meteorological Society. ISSN 1477-870X doi: https://doi.org/10.1002/qj.4140 (In Press)

Al Daas, H., Rees, T. and Scott, J. ORCID: https://orcid.org/0000-0003-2130-1091 (2021) Two-level Nystrom-Schur preconditioner for sparse symmetric positive definite matrices. SIAM Journal on Scientific Computing. ISSN 1095-7197 (In Press)

Scott, J. and Tuma, M. (2020) Strengths and limitations of stretching for least-squares problems with some dense rows. ACM Transactions on Mathematical Software (TOMS), 47 (1). pp. 1-25. ISSN 0098-3500 doi: https://doi.org/10.1145/3412559

Dauzickaite, I., Lawless, A. S., Scott, J. A. and Van Leeuwen, P. J. (2020) Spectral estimates for saddle point matrices arising in weak constraint four-dimensional variational data assimilation. Numerical Linear Algebra with Applications, 27 (5). ISSN 1099-1506 doi: https://doi.org/10.1002/nla.2313

Gould, N. I.M., Rees, T. and Scott, J. (2019) Convergence and evaluation-complexity analysis of a regularized tensor-Newton method for solving nonlinear least-squares problems. Computational Optimization and Applications, 73 (1). pp. 1-35. ISSN 0926-6003 doi: https://doi.org/10.1007/s10589-019-00064-2

Scott, J. and Tuma, M. (2019) Sparse stretching for solving sparse-dense linear least-squares problems. SIAM Journal on Scientific Computing, 41 (3). A1604-A1625. ISSN 1095-7197 doi: https://doi.org/10.1137/18M1181353

Scott, J. and Tuma, M. (2018) A Schur complement approach to preconditioning sparse linear least-squares problems with some dense rows. Numerical Algorithms, 79 (4). pp. 1147-1168. ISSN 1572-9265 doi: https://doi.org/10.1007/s11075-018-0478-2

Chow, E., Hartwig, A., Scott, J. and Dongarra, J. (2018) Using Jacobi iterations and blocking for solving sparse triangular systems in incomplete factorization preconditioning. Journal of Parallel and Distributed Computing, 119. pp. 219-230. ISSN 0743-7315 doi: https://doi.org/10.1016/j.jpdc.2018.04.017

Rees, T. and Scott, J. (2018) A comparative study of null-space factorizations for sparse symmetric saddle point systems. Numerical Linear Algebra with Applications, 25 (1). e2103. ISSN 1099-1506 doi: https://doi.org/10.1002/nla.2103

Lungten, S., Schilders, W. H. A. and Scott, J. A. (2018) Preordering saddle-point systems for sparse LDLT factorization without pivoting. Numerical Linear Algebra with Applications, 25 (5). e2173. ISSN 1099-1506 doi: https://doi.org/10.1002/nla.2173

Hook, J., Scott, J., Tisseur, F. and Hogg, J. (2018) A max-plus approach to incomplete Cholesky factorization preconditioners. SIAM Journal on Scientific Computing, 40 (4). A1987-A2004. ISSN 1095-7197 doi: https://doi.org/10.1137/16M1107735

Scott, J. and Tuma, M. (2017) Improving the stability and robustness of incomplete symmetric indefinite factorization preconditioners. Numerical Linear Algebra with Applications, 24 (5). e2099. ISSN 1099-1506 doi: https://doi.org/10.1002/nla.2099

Hogg, J., Scott, J. and Thorne, S. (2017) Numerically-aware orderings for sparse symmetric indefinite linear systems. ACM Transactions on Mathematical Software (TOMS), 44 (2). pp. 1-22. ISSN 0098-3500 doi: https://doi.org/10.1145/3104991

Scott, J. and Gould, N. (2017) The state-of-the-art of preconditioners for sparse linear least-squares problems. ACM Transactions on Mathematical Software (TOMS), 43 (4). 36. ISSN 0098-3500 doi: https://doi.org/10.1145/3014057

Scott, J. (2017) On using Cholesky-based factorizations and regularization for solving rank-deficient sparse linear least-squares problems. SIAM Journal on Scientific Computing, 39 (4). C319-C339. ISSN 1095-7197 doi: https://doi.org/10.1137/16M1065380

Scott, J. and Tuma, M. (2017) Solving mixed sparse-dense linear least-squares problems by preconditioned iterative methods. SIAM Journal on Scientific Computing, 39 (6). A2422-A2437. ISSN 1095-7197 doi: https://doi.org/10.1137/16M1108339

Dunning, P. D., Ovtchinnikov, E., Scott, J. and Kim, H. A. (2016) Level-set topology optimization with many linear buckling constraints using an efficient and robust eigensolver. International Journal for Numerical Methods in Engineering, 107 (12). pp. 1029-1053. ISSN 0029-5981 doi: https://doi.org/10.1002/nme.5203

Gould, N. and Scott, J. (2016) A note on performance profiles for benchmarking software. ACM Transactions on Mathematical Software (TOMS), 43 (2). 15. ISSN 0098-3500 doi: https://doi.org/10.1145/2950048

Hogg, J. D., Ovtchinnikov, E. and Scott, J. A. (2016) A sparse symmetric indefinite direct solver for GPU architectures. ACM Transactions on Mathematical Software (TOMS), 42 (1). 1. ISSN 0098-3500 doi: https://doi.org/10.1145/2756548

Scott, J. and Tuma, M. (2016) Preconditioning of linear least squares by robust incomplete factorization for implicitly held normal equations. SIAM Journal on Scientific Computing, 38 (6). C603-C623. ISSN 1095-7197 doi: https://doi.org/10.1137/16M105890X