2 papers
eess.SY2026
Improved Initialization for Port-Hamiltonian Neural Network Models
G. J. E. van Otterdijk, S. Weiland, M. Schoukens
Port-Hamiltonian neural networks have shown promising results in the identification of nonlinear dynamics of complex systems, as their combination of physical principles with data-…
eess.SY2024
Learning Subsystem Dynamics in Nonlinear Systems via Port-Hamiltonian Neural Networks
G. J. E. van Otterdijk, S. Moradi, S. Weiland +3
Port-Hamiltonian neural networks (pHNNs) are emerging as a powerful modeling tool that integrates physical laws with deep learning techniques. While most research has focused on mo…