- N. J. Higham and T. Mary, A New Approach Probabilistic Rounding Error Analysis, MIMS EPrint 2018.33, 2018.
- L. Ellam, G. Pavliotis, M. Girolami, A. Wilson, Stochastic modelling of urban structure, Proc. R. Soc. A, rspa.2017.0700, 2018.
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N. J. Higham and T. Mary. A new preconditioner that exploits low-rank approximations to factorization error, MIMS EPrint 2018.10, April 2018.
- W. Fang and M. B. Giles, Multilevel Monte Carlo Method for Ergodic SDEs without Contractivity, arXiv:1803.05932, 2018.
- M. Croci, M. B. Giles, M. E. Rognes, P. E. Farrell, Efficient white noise sampling and coupling for multilevel Monte Carlo with non-nested meshes, arXiv:1803.04857, 2018.
- M. B. Giles, Multilevel Monte Carlo methods, Acta Numerica, 10.1017/S09624929, 2018.
- E. Carson and N, J. Higham, Accelerating the Solution of Linear Systems by Iterative Refinement in Three Precisions, SIAM J. Sci. Comput., 40(2), A817–A847, 2018.
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H. Anzt, J. Dongarra, G. Flegar, N. J. Higham and E. S. Quintana-Orti, Adaptive Precision in Block-Jacobi Preconditioning for Iterative Sparse Linear System Solvers, Concurrency Computat.: Pract. Exper., 2018.
- C. F. Higham and D. J. Higham. Deep Learning: An Introduction for Applied Mathematicians, arXiv:1801.05894, 2018.
- E. Carson and N. J. Higham. A new analysis of iterative refinement and its application to accurate solution of ill-conditioned sparse linear systems, SIAM J. Sci. Comput., 39(6):A2834-A2856, 2017.
- L. Ellam, H. Strathmann, M. Girolami and I. Murray, A determinant-free method to simulate the parameters of large Gaussian fields, Stat, 6(1), 271-281, 2017.
- W. Fang and M. B. Giles, Adaptive Euler-Maruyama method for SDEs with non-globally Lipschitz drift: Part II, infinite time interval, arXiv:1703.06743, 2017.
- W. Fang and M. B. Giles, Adaptive Euler-Maruyama Method for SDEs with Non-globally Lipschitz Drift: Part I, Finite Time Interval, arXiv:1609.0810, 2016.
