automl/SMAC3: papers linking to it

GitHub · 1,267 stars · 248 forks · Python · created 2016 · github.com/automl/SMAC3

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to automl/SMAC3 (https://github.com/automl/SMAC3), 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#

4 papers in the tracked journals link to the GitHub repository automl/SMAC3 in their Crossref records, the first in 2021; most of them (2) in 2021.
By category: Operations Research (3) and AI (1); the journals with the most are Journal of Heuristics (2), Journal of Scheduling (1) and Data Mining and Knowledge Discovery (1).

By year#

20212024

Papers linking to automl/SMAC3 by publication year
Year	Papers
2021	2
2022	1
2024	1

Journals#

Journals whose papers link to automl/SMAC3 most
Journal	Papers
Journal of Heuristics	2
Journal of Scheduling	1
Data Mining and Knowledge Discovery	1

Papers linking to automl/SMAC3, most cited first
Published	Title	Journal	Authors	Citations	Link
2024-11-22	Hybridizing constraint programming and meta-heuristics for multi-mode resource-constrained multiple projects scheduling Problem	Journal of Heuristics	Arben Ahmeti, Nysret Musliu	12	cites it
2021-08-16	MultiETSC: automated machine learning for early time series classification	Data Mining and Knowledge Discovery	Gilles B. Ottervanger, Mitra Baratchi, Holger H. Hoos	10	cites it
2022-04-05	Exact and meta-heuristic approaches for the production leveling problem	Journal of Scheduling	Johannes Vass, Marie-Louise Lackner, Christoph Mrkvicka et al.	7	cites it
2021-08-02	Multi-level evolution strategies for high-resolution black-box control	Journal of Heuristics	Ofer M. Shir, Xi. Xing, HERSCHEL A. RABITZ	4	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). automl/SMAC3: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-automl-smac3

@misc{scholar4ai-code-github-automl-smac3,
  author = {{Scholar4AI}},
  title = {automl/SMAC3: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-automl-smac3}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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