autoencoder (R package): papers linking to it

CRAN · CRAN.R-project.org/package=autoencoder

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to autoencoder (R package) (https://CRAN.R-project.org/package=autoencoder), 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 autoencoder (R package) in their Crossref records, the first in 2017; most of them (1) in 2026.
By category: AI (2) and Information Systems (1); the journals with the most are Journal of Computational Social Science (1), Information Fusion (1) and Knowledge-Based Systems (1).
2 of the papers build on one another: a later paper cites an earlier one that also links autoencoder (R package).

By year#

20172026

Papers linking to autoencoder (R package) by publication year
Year	Papers
2017	1
2019	1
2026	1

Journals#

Journals whose papers link to autoencoder (R package) most
Journal	Papers
Journal of Computational Social Science	1
Information Fusion	1
Knowledge-Based Systems	1

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines Information Fusion, 2017
- Ruta: Implementations of neural autoencoders in R Knowledge-Based Systems, 2019 — cites the paper above

Papers linking to autoencoder (R package), most cited first
Published	Title	Journal	Authors	Citations	Link
2017-12-23	A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines	Information Fusion	David Charte, Francisco Charte, Salvador García et al.	306	cites it
2019-03-15	Ruta: Implementations of neural autoencoders in R	Knowledge-Based Systems	David Charte, Francisco Herrera, Francisco Charte	6	cites it
2026-10-22	Synthetic data publishing using Bayesian Network: a case study of COVID-19 patients data in Jakarta, Indonesia	Journal of Computational Social Science	Bahrul Ilmi Nasution, Yudhistira Nugraha, Muhammad Erza Aminanto et al.	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). autoencoder (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-autoencoder

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

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