scikit-learn/scikit-learn: papers linking to it

GitHub · 67,986 stars · 27,630 forks · Python · license BSD-3-Clause · created 2010 · github.com/scikit-learn/scikit-learn

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to scikit-learn/scikit-learn (https://github.com/scikit-learn/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#

3 papers in the tracked journals link to the GitHub repository scikit-learn/scikit-learn in their Crossref records, the first in 2018; most of them (1) in 2025.
By category: Operations Research (2) and AI (1); the journals with the most are Transportation Research Part C Emerging Technologies (1), Operations Research Forum (1) and Knowledge-Based Systems (1).

By year#

20182025

Papers linking to scikit-learn/scikit-learn by publication year
Year	Papers
2018	1
2020	1
2025	1

Journals#

Journals whose papers link to scikit-learn/scikit-learn most
Journal	Papers
Transportation Research Part C Emerging Technologies	1
Operations Research Forum	1
Knowledge-Based Systems	1

Papers linking to scikit-learn/scikit-learn, most cited first
Published	Title	Journal	Authors	Citations	Link
2020-06-15	Real-time crash prediction on expressways using deep generative models	Transportation Research Part C Emerging Technologies	Qing Cai, Mohamed A. Abdel-Aty, Jinghui Yuan et al.	205	cites it
2018-04-21	PySEF: A python library for similarity-based dimensionality reduction	Knowledge-Based Systems	Nikolaos Passalis, Anastasios Tefas	5	cites it
2025-12-05	How Robust Are Different Versions of Graphical Model Selection Algorithms	Operations Research Forum	Kostylev Ilya, Kalyagin Valeriy	0	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/scikit-learn: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-scikit-learn-scikit-learn

@misc{scholar4ai-code-github-scikit-learn-scikit-learn,
  author = {{Scholar4AI}},
  title = {scikit-learn/scikit-learn: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-scikit-learn-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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