1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2025
Data Denoising and Derivative Estimation for Data-Driven Modeling of Nonlinear Dynamical Systems
Jiaqi Yao, Lewis Mitchell, John Maclean +1
Data-driven modeling of nonlinear dynamical systems is often hampered by measurement noise. We propose a denoising framework, called Runge-Kutta and Total Variation Based Implicit…
math.DS2024★ 1 cited
Unifying Lyapunov exponents with probabilistic uncertainty quantification
Liam Blake, John Maclean, Sanjeeva Balasuriya
The Lyapunov exponent is well-known in deterministic dynamical systems as a measure for quantifying chaos and detecting coherent regions in physically evolving systems. In this Let…
math.DS2023
The convergence of stochastic differential equations to their linearisation in small noise limits
Liam Blake, John Maclean, Sanjeeva Balasuriya
Prediction via deterministic continuous-time models will always be subject to model error, for example due to unexplainable phenomena, uncertainties in any data driving the model,…