Blealtan/efficient-kan: papers linking to it

GitHub · 4,662 stars · 415 forks · Python · license MIT · created 2024 · github.com/Blealtan/efficient-kan

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to Blealtan/efficient-kan (https://github.com/Blealtan/efficient-kan), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

Key findings#

3 papers in the tracked journals link to the GitHub repository Blealtan/efficient-kan in their Crossref records, the first in 2025; most of them (3) in 2025.
By category: AI (3); the journals with the most are Neural Networks (2) and Expert Systems with Applications (1).

By year#

20252025

Papers linking to Blealtan/efficient-kan by publication year
Year	Papers
2025	3

Journals#

Journals whose papers link to Blealtan/efficient-kan most
Journal	Papers
Neural Networks	2
Expert Systems with Applications	1

Papers linking to Blealtan/efficient-kan, most cited first
Published	Title	Journal	Authors	Citations	Link
2025-07-19	LeanKAN: a parameter-lean Kolmogorov-Arnold network layer with improved memory efficiency and convergence behavior	Neural Networks	Benjamin C. Koenig, Suyong Kim, Sili Deng	14	cites it
2025-01-26	Incremental energy-based recurrent transformer-KAN for time series deformation simulation of soft tissue	Expert Systems with Applications	Jiaxi Jiang, Tianyu Fu, Jiaqi Liu et al.	12	cites it
2025-11-03	asKAN: Active subspace embedded Kolmogorov-Arnold network	Neural Networks	Zhiteng Zhou, Zhaoyue Xu, Yi Liu et al.	3	cites it

How this is measured#

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

Cite this page

Scholar4AI. (2026). Blealtan/efficient-kan: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-blealtan-efficient-kan

@misc{scholar4ai-code-github-blealtan-efficient-kan,
  author = {{Scholar4AI}},
  title = {Blealtan/efficient-kan: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-blealtan-efficient-kan}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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