Our work on discovering nonlinear dynamical systems using a Runge–Kutta-inspired dictionary-based sparse regression approach has been published in the proceedings of the Royal Society A: Mathematical, physical and engineering science. This work demonstrated that blending numerical integration schemes with sparse regression enhances the performance, particularly for noisy and sparse data.