Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework
B. Bachmann, L. Bonaventura, F. Casella, S. Fernández-García, M. Gómez-Mármol, P. Hannebohm, Journal of Scientific Computing 105 (2025).

Residual-Informed Learning of Solutions to Algebraic Loops
F. Brandt, A. Heuermann, P. Hannebohm, B. Bachmann, ArXiv:2510.09317 (2025).

Diagnosing Newton’s Solver Convergence Failures in the Initialization of Modelica Models
F. Casella, B. Bachmann, K. Abdelhak, P. Hannebohm, T. Van der Stelt, in: Proceedings of the 16th International Modelica&;FMI Conference, September 8 – 10, 2025, Lucerne University of Applied Sciences and Arts (HSLU), Linköping University Electronic Press, 2025.

Selective Evaluation of RHS during Multi-Rate Simulation
P. Hannebohm, B. Bachmann, in: D. Zimmer, U.C. Müller (Eds.), Proceedings of the 16th International Modelica&;FMI Conference, Linköping University Electronic Press, 2025, pp. 943–947.

Efficient Training of Physics-enhanced Neural ODEs via Direct Collocation and Nonlinear Programming
L. Langenkamp, P. Hannebohm, B. Bachmann, in: D. Zimmer, U.C. Müller (Eds.), Proceedings of the 16th International Modelica&;FMI Conference, Linköping University Electronic Press, 2025, pp. 445–457.

Accelerating the simulation of equation-based models by replacing non-linear algebraic loops with error-controlled machine learning surrogates
A. Heuermann, P. Hannebohm, M. Schäfer, B. Bachmann, in: D. Müller, A. Monti, A. Benigni (Eds.), Proceedings of the 15th International Modelica Conference 2023, Aachen, October 9-11, Linköping University Electronic Press, 2023, pp. 275–284.

Fehlerkontrollierte ML-Surrogate zur beschleunigten Simulation nichtlinearer Gleichungssysteme in Modelica
A. Heuermann, P. Hannebohm, M. Schäfer, B. Bachmann, in: Unpublished, 2023.