mlsanityData to 7 Oct 2026

Weihrauch Complexity in Computable Analysis

arXiv 1707.03202 ↗First posted 11 Jul 2017math.LO cs.LOcited by 4

Not on the map. Why?

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.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Jul 2017.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 0; 2023: 1; 2024: 0; 2025: 0; 2026: 1.

4 papers.

  1. 2021A Computability Perspective on (Verified) Machine Learningcited by 3
  2. 2021On computable learning of continuous featurescited by 2
  3. 2023On the Complexity of Computing G"odel Numberscited by 0
  4. 2026Uniform Computability of PAC Learningcited by 0