Laplacian eigenfunction-based neural operators approximate the solution operator of the generalized Gierer-Meinhardt reaction-diffusion system with error bounds that imply only polynomial growth in parameters as accuracy improves.
For the second term, (15) yields |(2)| ≤ ∥ ˜G∥W 1,∞ Z t 0 Z Ω |Φ(x, y, t−s)−Φ N(x, y, t−s)|dy ds≲ϵ
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Approximation Theory of Laplacian-Based Neural Operators for Reaction-Diffusion System
Laplacian eigenfunction-based neural operators approximate the solution operator of the generalized Gierer-Meinhardt reaction-diffusion system with error bounds that imply only polynomial growth in parameters as accuracy improves.