tdiethe/gunnar_raetsch_benchmark_datasets: papers linking to it

GitHub · 5 stars · 0 forks · license MIT · created 2015 · github.com/tdiethe/gunnar_raetsch_benchmark_datasets

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to tdiethe/gunnar_raetsch_benchmark_datasets (https://github.com/tdiethe/gunnar_raetsch_benchmark_datasets), 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 tdiethe/gunnar_raetsch_benchmark_datasets in their Crossref records, the first in 2019; most of them (2) in 2022.
By category: AI (2) and Statistics (1); the journals with the most are Expert Systems with Applications (1), Machine Learning (1) and Statistics and Computing (1).

By year#

20192022

Papers linking to tdiethe/gunnar_raetsch_benchmark_datasets by publication year
Year	Papers
2019	1
2022	2

Journals#

Journals whose papers link to tdiethe/gunnar_raetsch_benchmark_datasets most
Journal	Papers
Expert Systems with Applications	1
Machine Learning	1
Statistics and Computing	1

Papers linking to tdiethe/gunnar_raetsch_benchmark_datasets, most cited first
Published	Title	Journal	Authors	Citations	Link
2019-06-27	Combining hierarchical clustering approaches using the PCA method	Expert Systems with Applications	Mohammad Jafarzadegan, Faramarz Safi-Esfahani, Zahra Beheshti	143	cites it
2022-10-19	Parametric non-parallel support vector machines for pattern classification	Machine Learning	Sambhav Jain, Reshma Rastogi	25	cites it
2022-11-23	Bayesian learning via neural Schrödinger–Föllmer flows	Statistics and Computing	Francisco Vargas, Andrius Ovsianas, David Fernandes et al.	7	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). tdiethe/gunnar_raetsch_benchmark_datasets: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-tdiethe-gunnar-raetsch-benchmark-datasets

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

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