Research

This page lists selected publications by topic. For a complete and frequently updated list, please see my Google Scholar profile.

Randomised numerical schemes

• J. Bao and Y. Wu, Randomised Euler-Maruyama method for SDEs with Hölder continuous drift coefficient, BIT Numerical Mathematics, 65 (2025).
• P. Przybyłowicz, Y. Wu and X. Xie, On approximation of solutions of stochastic delay differential equations via randomized Euler scheme, Applied Numerical Mathematics, 197 (2024), 143-163.
• F. V. Difonzo, P. Przybyłowicz, Y. Wu and X. Xie, A Randomized Runge-Kutta Method for time-irregular delay differential equations, arXiv preprint.
• F. V. Difonzo, P. Przybyłowicz and Y. Wu, Existence, uniqueness and approximation of solutions to Carathéodory delay differential equations, Journal of Computational and Applied Mathematics, 436 (2024), 115411.
• Y. Wu, A randomised trapezoidal quadrature. International Journal of Computer Mathematics, 99.4 (2022): 680-692.
• Y. Wu and N. Polydorides, A multilevel Monte Carlo estimator for matrix multiplication, SIAM Journal on Scientific Computing, 42.5 (2020), A2731-A2749.
• R. Lung, Y. Wu, D. Kamilis and N. Polydorides, A sketched finite element method for elliptic models, Computer Methods in Applied Mechanics and Engineering, 364(2020), 112933.
• R. Kruse, N. Polydorides and Y. Wu, Application of randomized quadrature Formulas to the finite element method for elliptic equations, arXiv preprint.
• R. Kruse and Y. Wu, A randomized Galerkin finite element method for SEE, Mathematics of Computation, 88 (2019), 2793-2825.
• R. Kruse and Y. Wu, A randomized Milstein method for stochastic differential equations with non-differentiable drift coefficients, Discrete and Continuous Dynamical Systems - Series B, 24.8 (2019): 3475-3502.
• R. Kruse and Y. Wu, Error analysis of randomized Runge-Kutta methods for differential equations with time irregular coefficients, Computational Methods in Applied Mathematics, 17.3 (2017), 479-498.

Random periodic solutions

• Y. Guo, C. Pang, X. Wang and Y. Wu, Order-one explicit approximations of random periodic solutions of semi-linear SDEs with multiplicative noise, Communications in Nonlinear Science and Numerical Simulation, 152 (2026), 109386.
• Y. Guo, X. Wang and Y. Wu, Order-one convergence of the backward Euler method for random periodic solutions of semilinear SDEs, Discrete and Continuous Dynamical Systems - Series B, 30 (2025), 3222-3242.
• J. Bao and Y. Wu, Random periodic solutions for stochastic differential equations with non-uniform dissipativity, arXiv preprint.
• Y. Wu and C. Yuan, The Galerkin analysis for the random periodic solution of semilinear stochastic evolution equations, Journal of Theoretical Probability, (2023).
• Y. Wu, Backward Euler–Maruyama Method for the Random Periodic Solution of a Stochastic Differential Equation with a Monotone Drift, Journal of Theoretical Probability, (2022).
• C. Feng, Y. Wu and H. Zhao, Pathwise anticipating random periodic solutions-II.SPDEs with multiplicative linear noise, arXiv preprint.
• C. Feng, Y. Wu and H. Zhao, Anticipating random periodic solutions-I. SDEs with multiplicative linear noise, Journal of Functional Analysis, 271 (2016), 365-417.

Rough path theory and its applications in machine learning

• R. Ibraheem, Y. Wu, T. Lyons and G. dos Reis, Early prediction of Lithium-ion cell degradation trajectories using signatures of voltage curves up to 4-minute sub-sampling rates, Applied Energy, 352 (2023), 121974.
• B. Fang, H. Ni and Y. Wu, A Neural RDE-based model for solving path-dependent PDEs, arXiv preprint.
• Y. Wu, G.M. Goodwin, T. Lyons and K.E.A. Saunders, Identifying psychiatric diagnosis from missing mood data through the use of log-signature features, PLOS ONE, 7.11 (2022), e0276821.
• P. Moore, T. Iliant, F. Ion, Y. Wu and T.J. Lyons, Path signatures for non-intrusive load monitoring, In ICASSP 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, 2022.
• Y. Wu, H. Ni, T.J. Lyons and R.L. Hudson, Signature features with visibility transformation, In 2020 25th International Conference on Pattern Recognition (ICPR), 4665-4672. IEEE, 2021.
• B. Wang, Y. Wu, N. Vaci, M. Liakata , T. Lyons, and K. Saunders, Modelling Paralinguistic Properties in Conversational Speech to Detect Bipolar Disorder and Borderline Personality Disorder, In ICASSP 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 7243-7247, IEEE, 2021.
• B. Wang, Y. Wu, N. Taylor, T. Lyons, M. Liakata, A. J. Nevado-Holgado and K.Saunders, Learning to detect bipolar disorder and borderline personality disorder with language and speech in non-clinical Interviews, In Proc.Interspeech 2020, 437-441. 2020.
• S. Riedel and Y. Wu, Semi-implicit Taylor schemes for stiff rough differential equations, arXiv preprint.
• R. L. Hudson, U. Schauz and Y. Wu, Moments of quantum Lévy area using sticky shuffle Hopf algebra, Annales de l’Institut Henri Poincaré D, 5.3 (2018), 437-466.
• R. L. Hudson, U. Schauz and Y. Wu, The moment of Lévy area using sticky shuffle Hopf algebra, Communications on Stochastic Analysis, 11.3 (2017), 287-299.

Other numerics

• C. Pang, X. Wang and Y. Wu, Projected Langevin Monte Carlo algorithms in non-convex and super-linear setting, Journal of Computational Physics, 526 (2025), 113754.
• C Pang, X Wang, and Y. Wu, Linear implicit approximations of invariant measures of semi-linear SDEs with non-globally Lipschitz coefficients, Journal of Complexity, (2024), p.101842.
• X. Xie, Y. Wu, H. Ni and C. He, NODE-ImgNet: a PDE-informed effective and robust model for image denoising, Pattern Recognition, 148 (2024), 110176.
• W. Liu, X. Mao and Y. Wu, The backward Euler-Maruyama method for invariant measures of stochastic differential equations with super-linear coefficients, Applied Numerical Mathematics, 184 (2023), 137-150.
• P.V. Oliva, Y. Wu, C. He and H. Ni, Towards fast weak adversarial training to solve high dimensional parabolic partial differential equations using XNODE-WAN, Journal of Computational Physics, 463 (2022), 111233.
• W. Liu, X. Mao, J. Tang, and Y. Wu, Truncated Euler-Maruyama method for classical and time-changed non-autonomous stochastic differential equations, Applied Numerical Mathematics, 153 (2020), 66-81.

Data science applications

• Y. Wu and collaborators, DECOVID: A UK two-center harmonized database of acute care electronic health records for COVID-19 research, Data, 10 (2025).