bd2kccd/r-causal: papers linking to it

GitHub · 36 stars · 20 forks · Java · created 2016 · github.com/bd2kccd/r-causal

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to bd2kccd/r-causal (https://github.com/bd2kccd/r-causal), 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 bd2kccd/r-causal in their Crossref records, the first in 2022; most of them (2) in 2022.
By category: AI (3); the journals with the most are Data Mining and Knowledge Discovery (1), Knowledge and Information Systems (1) and Machine Learning (1).

By year#

20222024

Papers linking to bd2kccd/r-causal by publication year
Year	Papers
2022	2
2024	1

Journals#

Journals whose papers link to bd2kccd/r-causal most
Journal	Papers
Data Mining and Knowledge Discovery	1
Knowledge and Information Systems	1
Machine Learning	1

Papers linking to bd2kccd/r-causal, most cited first
Published	Title	Journal	Authors	Citations	Link
2022-03-16	Partitioned hybrid learning of Bayesian network structures	Machine Learning	Jireh Huang, Qing Zhou	13	cites it
2022-11-28	Hybrid Bayesian network discovery with latent variables by scoring multiple interventions	Data Mining and Knowledge Discovery	Kiattikun Chobtham, Anthony Costa Constantinou, Neville Kenneth Kitson	9	cites it
2024-05-24	Tuning structure learning algorithms with out-of-sample and resampling strategies	Knowledge and Information Systems	Kiattikun Chobtham, Anthony Costa Constantinou	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). bd2kccd/r-causal: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-bd2kccd-r-causal

@misc{scholar4ai-code-github-bd2kccd-r-causal,
  author = {{Scholar4AI}},
  title = {bd2kccd/r-causal: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-bd2kccd-r-causal}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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