Symplectic Neural Operators preserve symplectic structure for learning infinite-dimensional Hamiltonian PDEs and deliver improved long-term energy stability in theory and experiments.
Proceedings of the American Mathematical Society , volume =
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.DS 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Symplectic Neural Operators for Learning Infinite Dimensional Hamiltonian Systems
Symplectic Neural Operators preserve symplectic structure for learning infinite-dimensional Hamiltonian PDEs and deliver improved long-term energy stability in theory and experiments.