Ueber die numerische Auflösung von Differentialgleichungen

By C. Runge. 1895

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Neural Ordinary Differential Equations (2018, neutral): “There have since been more than 120 years of development of ef ﬁ cient and accurate ODE solvers (Runge, 1895; Kutta, 1901; Hairer et al., 1987).”
Numerical Gaussian Processes for Time-Dependent and Nonlinear Partial Differential Equations (2017, methodology): “This last equality reveals a key feature of this Runge-Kutta numerical Gaussian process, namely the fact that it inspects the same data through the lens of different kernels.”
RUN beyond the metaphor: An efficient optimization algorithm based on Runge Kutta method (2021, methodology): “…Runge Kutta optimizer (RUN), was designed according to the foundations of the Runge Kutta method 3 (Kutta, 1901; 1 https://aliasgharheidari.com/SMA.html 2 https://aliasgharheidari.com/HHO.html 3 For a better presentation of the term, we use the term Runge Kutta in this paper Runge, 1895).”
Learning Differential Equations that are Easy to Solve (2020, methodology): “Adaptive-step Runge-Kutta ODE Solvers Runge-Kutta methods (Runge, 1895; Kutta, 1901) approximate the solution trajectories of ODEs through a series of small steps, starting at time t 0 .”