# Weihrauch Complexity in Computable Analysis

arXiv: https://arxiv.org/abs/1707.03202 · HTML: https://mlsanity.com/paper/1707.03202/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Jul 2017.

## Built on by (most cited first, 4 of 4)

- [A Computability Perspective on (Verified) Machine Learning](https://mlsanity.com/paper/2102.06585/) (2021)
- [On computable learning of continuous features](https://mlsanity.com/paper/2111.14630/) (2021)
- [On the Complexity of Computing G"odel Numbers](https://mlsanity.com/paper/2302.04213/) (2023)
- [Uniform Computability of PAC Learning](https://mlsanity.com/paper/2601.18663/) (2026)

## Abstract (arXiv)

We provide a self-contained introduction into Weihrauch complexity and its applications to computable analysis. This includes a survey on some classification results and a discussion of the relation to other approaches.