Derives discretization error bounds and input-to-state stability guarantees for SS-NOs and FNOs, with empirical validation on 1D and 2D PDE benchmarks.
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
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Stability and Discretization Error of State Space Model Neural Operators
Derives discretization error bounds and input-to-state stability guarantees for SS-NOs and FNOs, with empirical validation on 1D and 2D PDE benchmarks.