2 papers
cs.LG2026
CoSynFlow: Conformal Symplectic Neural Flows for Cross-System Prediction of Dissipative Hamiltonian Dynamics
Baige Xu, Takaharu Yaguchi
Learning solution operators for differential equations is a central problem in scientific machine learning. However, many neural operator methods optimize prediction accuracy witho…
cs.LG2025
Learning Hamiltonian Density Using DeepONet
Baige Xu, Yusuke Tanaka, Takashi Matsubara +1
In recent years, deep learning for modeling physical phenomena which can be described by partial differential equations (PDEs) have received significant attention. For example, for…