Spectral Convergence of Random Feature Method in Multiple Dimensions
math.NA, cs.AI, cs.LG, cs.NA, math.ST, stat.TH
Submitted: 2026-09-03
Updated: 2026-09-03
Comments: 48 pages, 1 figure, 2 tables
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Approximation Theory and Applications of Randomized Neural Networks for Solving High-Dimensional PDEs
- Trace Regularity PINNs: Enforcing $\mathrm{H}^{\frac{1}{2}}(\partial \Omega)$ for Boundary Data
- A Structure-Adaptive Random Feature Method for High-Dimensional Elliptic PDEs
- Optimal Rates and Saturation for Noiseless Kernel Ridge Regression
- Spectral connvergece of random feature method in one dimension
- On the Approximation Properties of Random ReLU Features
- SSBE-PINN: A Sobolev Boundary Scheme Boosting Stability and Accuracy in Elliptic/Parabolic PDE Learning
- A Discrete-Time Random Feature Method for Nonlinear Evolution Equations with Implicit-Explicit Runge--Kutta Time Stepping
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