Open access
Jul 2026
A Hybrid Physics-Augmented Neural Network for Dynamic System Modeling with Partially Known Dynamics
The experimental results in this application confirm that hybrid models yield superior performance over strict physical approaches and can implicitly approximate submodel dynamics within a unified, yet modular, architecture, opening avenues for applications in domains where partial physics-based knowledge is available but insufficient on its own.
Laurin Ludmann, Jaeyoun Choi, J. Neubeck et al.
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