3 papers
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…
math.NA2026
A Structure-Preserving Numerical Scheme for Optimal Control and Design of Mixing in Incompressible Flows
Weiwei Hu, Ziqian Li, Yubiao Zhang +1
We develop a structure-preserving computational framework for optimal mixing control in incompressible flows. Our approach exactly conserves the continuous system's key invariants…
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…