scikit-learn: papers linking to it

SourceForge · sourceforge.net/projects/scikit-learn/

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to scikit-learn (https://sourceforge.net/projects/scikit-learn/), 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#

5 papers in the tracked journals link to the SourceForge repository scikit-learn in their Crossref records, the first in 2022; most of them (1) in 2026.
By category: AI (3), Economics (1) and Higher Education and Research (1); the journals with the most are Expert Systems with Applications (2), Asia-Pacific Journal of Regional Science (1) and Scientometrics (1).

By year#

20222026

Papers linking to scikit-learn by publication year
Year	Papers
2022	1
2023	1
2024	1
2025	1
2026	1

Journals#

Journals whose papers link to scikit-learn most
Journal	Papers
Expert Systems with Applications	2
Asia-Pacific Journal of Regional Science	1
Scientometrics	1
Neural Computing and Applications	1

Papers linking to scikit-learn, most cited first
Published	Title	Journal	Authors	Citations	Link
2023-08-28	Multi-objective robust parameter optimization using the extended and weighted k-means (EWK-means) clustering in laser powder bed fusion (LPBF)	Expert Systems with Applications	Adrian Matias Chung Baek, Eunju Park, Minkyu Seong et al.	25	cites it
2025-04-16	Multi-objective optimization and predictive analytics of strength and embodied impacts of CDW-based geopolymers using various machine learning approaches	Neural Computing and Applications	Obaid Ur Rahman Mahmoodi, Hocine Siad, Mohamed Lachemi et al.	11	cites it
2024-07-09	Understanding and predicting lapses in mortgage life insurance using a machine learning approach	Expert Systems with Applications	Carlos Manteigas, Nuno António	5	cites it
2022-02-05	TeknoAssistant : a domain specific tech mining approach for technical problem-solving support	Scientometrics	Gaizka Garechana, Rosa María Río Belver, Enara Zarrabeitia Bilbao et al.	3	cites it
2026-05-20	Probabilistic vulnerability analysis of converted rice fields in the mamminasata urban area	Asia-Pacific Journal of Regional Science	Ahmad Firman Ashari, Risma Neswati, Samsu Arif	1	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). scikit-learn: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/sourceforge-scikit-learn

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

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