Yong‐Sheng Chen

Reduced-Order Modeling of Hamiltonian Dynamics Based on Symplectic Neural Networks

Abstract. We introduce a novel data-driven symplectic reduced-order modeling (ROM) framework for high-dimensional Hamiltonian systems that unifies latent-space discovery and dynamics learning within a single, end-to-end neural architecture. The encoder–decoder is built from Hénon...