Learning PDE Dynamics between Submanifolds Using Green's Observation Operators
cs.LG
Submitted: 2026-10-01
Updated: 2026-10-05
Sources
- Learning Dynamical Systems from Partial Observations
- Physics-informed neural networks for transformed geometries and manifolds
- Global Optimality in Tensor Factorization, Deep Learning, and Beyond
- SPFNO: Spectral operator learning for PDEs with Dirichlet and Neumann boundary conditions
- Neural-POD: A Plug-and-Play Neural Operator Framework for Infinite-Dimensional Functional Nonlinear Proper Orthogonal Decomposition
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