Covers numerical methods for solving differential equations and their stability analysis, focusing on error calculation and practical applications in engineering and science.
Explores error estimation in numerical methods for solving differential equations, focusing on local truncation error, stability, and Lipschitz continuity.
Explores explicit stabilised Runge-Kutta methods and their application to Bayesian inverse problems, covering optimization, sampling, and numerical experiments.
