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Neural Approximation by Function Composition: Rigidity and Doubly Exponential Convergence
Deep neural networks approximate functions by composing affine maps with nonlinear activations, but how composition itself creates approximation power is not yet fully understood. We investigate a fundamental mechanism: geometrically weighted sums of iterates of a single scalar generator function. T
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