mlsanityData to 7 Oct 2026

Approximation error of single hidden layer neural networks with fixed weights

arXiv 2202.03289 ↗First posted 7 Feb 2022cs.LG math.CA stat.MLcited by 2

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Abstract (arXiv)

This paper provides an explicit formula for the approximation error of single hidden layer neural networks with two fixed weights.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 2 of its 53 references that are in the map. First posted on arXiv 7 Feb 2022.

Builds on

2 of 53 references.

References · 2

  1. 2021Approximation capability of two hidden layer feedforward neural networks with fixed weightscited by 24
  2. 2017On the approximation by single hidden layer feedforward neural networks with fixed weightscited by 19

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Citing papers per year: 2024: 2.

2 papers.

  1. 2024Universal Approximation Theorem for Vector- and Hypercomplex-Valued Neural Networkscited by 11
  2. 2024Addressing common misinterpretations of KART and UAT in neural network literaturecited by 9