Pages that link to "Item:Q2251472"
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The following pages link to Almost optimal estimates for approximation and learning by radial basis function networks (Q2251472):
Displaying 17 items.
- \(L^p\) approximation capability of RBF neural networks (Q944076) (← links)
- Complexity of Gaussian-radial-basis networks approximating smooth functions (Q998978) (← links)
- On simultaneous approximations by radial basis function neural networks (Q1294160) (← links)
- Relaxed conditions for radial-basis function networks to be universal approximators. (Q1422258) (← links)
- Radial basis reproducing kernel particle method for piezoelectric materials (Q1658806) (← links)
- The numerical analysis of piezoelectric ceramics based on the Hermite-type RPIM (Q1738110) (← links)
- Learning-based complexity evaluation of radial basis function networks (Q1857770) (← links)
- A comment on ``Relaxed conditions for radial-basis function networks to be universal approximators'' (Q1932117) (← links)
- Learning radial basis function networks with the trust region method for boundary problems (Q1992271) (← links)
- Nonlinear approximation via compositions (Q2185653) (← links)
- (Q4558477) (← links)
- The Hermit-Type Reproducing Kernel Particle Method for Elasticity Problems (Q4559364) (← links)
- (Q4736124) (← links)
- Deep Network Approximation Characterized by Number of Neurons (Q5162359) (← links)
- Approximating smooth and sparse functions by deep neural networks: optimal approximation rates and saturation (Q6062170) (← links)
- Learning sparse and smooth functions by deep sigmoid nets (Q6109261) (← links)
- Learning and approximating piecewise smooth functions by deep sigmoid neural networks (Q6634146) (← links)
