# Approximation error of single hidden layer neural networks with fixed weights

arXiv: https://arxiv.org/abs/2202.03289 · HTML: https://mlsanity.com/paper/2202.03289/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 53 references that are in the map.
- First posted on arXiv 7 Feb 2022.

## Builds on (most cited first, 2 of 2)

- [Approximation capability of two hidden layer feedforward neural networks with fixed weights](https://mlsanity.com/paper/2101.09181/) (2021)
- [On the approximation by single hidden layer feedforward neural networks with fixed weights](https://mlsanity.com/paper/1708.06219/) (2017)

## Built on by (most cited first, 2 of 2)

- [Universal Approximation Theorem for Vector- and Hypercomplex-Valued Neural Networks](https://mlsanity.com/paper/2401.02277/) (2024)
- [Addressing common misinterpretations of KART and UAT in neural network literature](https://mlsanity.com/paper/2408.16389/) (2024)

## Abstract (arXiv)

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