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cs.LG2026
Long-Time Trajectory Approximation via SA-NODEs: Model Predictive and Floquet Strategies
Ziqian Li, Nikolaos M. Matzakos
We study the approximation of dynamical systems by semi-autonomous neural ordinary differential equations (SA-NODEs) over long time horizons. For a single network trained on the wh…
cs.LG2025
Deep Neural ODE Operator Networks for PDEs
Ziqian Li, Kang Liu, Yongcun Song +2
Operator learning has emerged as a promising paradigm for developing efficient surrogate models to solve partial differential equations (PDEs). However, existing approaches often o…