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A Survey on Universal Approximation Theorems

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arxiv 2407.12895 v1 pith:D2ZMRA6R submitted 2024-07-17 cs.LG cs.SYeess.SY

classification cs.LGcs.SYeess.SY
keywords approximationtheoremtheoremsuatsuniversalarbitraryarnoldaspects
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This paper discusses various theorems on the approximation capabilities of neural networks (NNs), which are known as universal approximation theorems (UATs). The paper gives a systematic overview of UATs starting from the preliminary results on function approximation, such as Taylor's theorem, Fourier's theorem, Weierstrass approximation theorem, Kolmogorov - Arnold representation theorem, etc. Theoretical and numerical aspects of UATs are covered from both arbitrary width and depth.

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Cited by 6 Pith papers

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