---
title: "automl/SMAC3: papers citing this GitHub repository"
description: "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."
url: https://scholar4ai.com/code/github-automl-smac3
markdown_url: https://scholar4ai.com/code/github-automl-smac3.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "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. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# automl/SMAC3: papers linking to it

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.

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

All repositories: https://scholar4ai.com/code.md

## 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

*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](https://scholar4ai.com/journals/journal-of-heuristics.md) | 2 |
| [Journal of Scheduling](https://scholar4ai.com/journals/journal-of-scheduling.md) | 1 |
| [Data Mining and Knowledge Discovery](https://scholar4ai.com/journals/data-mining-and-knowledge-discovery.md) | 1 |

## Papers

*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](https://doi.org/10.1007/s10732-024-09540-3) | [Journal of Heuristics](https://scholar4ai.com/journals/journal-of-heuristics.md) | Arben Ahmeti, Nysret Musliu | 12 | cites it |
| 2021-08-16 | [MultiETSC: automated machine learning for early time series classification](https://doi.org/10.1007/s10618-021-00781-5) | [Data Mining and Knowledge Discovery](https://scholar4ai.com/journals/data-mining-and-knowledge-discovery.md) | Gilles B. Ottervanger, Mitra Baratchi, Holger H. Hoos | 10 | cites it |
| 2022-04-05 | [Exact and meta-heuristic approaches for the production leveling problem](https://doi.org/10.1007/s10951-022-00721-1) | [Journal of Scheduling](https://scholar4ai.com/journals/journal-of-scheduling.md) | 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](https://doi.org/10.1007/s10732-021-09483-z) | [Journal of Heuristics](https://scholar4ai.com/journals/journal-of-heuristics.md) | 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

```bibtex
@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}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).