SWAN-SF: papers linking to it

Harvard Dataverse · Dataset · 2020 · doi.org/10.7910/DVN/EBCFKM

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to SWAN-SF (https://doi.org/10.7910/DVN/EBCFKM), 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#

5 papers in the tracked journals link to the Harvard Dataverse dataset SWAN-SF in their Crossref records, the first in 2022; most of them (2) in 2026.
By category: AI (5); the journals with the most are Neural Networks (2), Expert Systems with Applications (1) and Neural Computing and Applications (1).
It is the own code or data of 1 paper here, the first “Anomaly detection in streaming data: A comparison and evaluation study” (Expert Systems with Applications, 2023).
4 of the papers build on one another: a later paper cites an earlier one that also links SWAN-SF, or uses the code an earlier paper published.

By year#

20222026

Papers linking to SWAN-SF by publication year
Year	Papers
2022	1
2023	1
2025	1
2026	2

Journals#

Journals whose papers link to SWAN-SF most
Journal	Papers
Neural Networks	2
Expert Systems with Applications	1
Neural Computing and Applications	1
Data Mining and Knowledge Discovery	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.

Anomaly detection in streaming data: A comparison and evaluation study Expert Systems with Applications, 2023
- CSTSINR: improving temporal continuity via convolutional structured implicit neural representations for time series anomaly detection Neural Networks, 2025 — uses the code or data the paper above published (without citing it)
- A noise robust and distribution-adaptive framework for multivariate time series anomaly detection Neural Networks, 2026 — uses the code or data the paper above published (without citing it)
- Value and shape-aware transformer with prior-enhanced self-attention for multivariate time series classification Data Mining and Knowledge Discovery, 2026 — uses the code or data the paper above published (without citing it)

Papers linking to SWAN-SF, most cited first
Published	Title	Journal	Authors	Citations	Link
2023-07-17	Anomaly detection in streaming data: A comparison and evaluation study	Expert Systems with Applications	Félix Iglesias, Alexander Hartl, Tanja Zseby et al.	35	own code or data
2022-05-30	CGAN-based synthetic multivariate time-series generation: a solution to data scarcity in solar flare forecasting	Neural Computing and Applications	Yang Chen, Dustin Kempton, Azim Ahmadzadeh et al.	18	cites it
2025-09-22	CSTSINR: improving temporal continuity via convolutional structured implicit neural representations for time series anomaly detection	Neural Networks	Ke Liu, Mengxuan Li, Jiajun Bu et al.	4	cites it
2026-02-10	A noise robust and distribution-adaptive framework for multivariate time series anomaly detection	Neural Networks	Yanling Du, Ziliang Yang, Baozeng Chang et al.	1	cites it
2026-06-18	Value and shape-aware transformer with prior-enhanced self-attention for multivariate time series classification	Data Mining and Knowledge Discovery	Wenjie Xi, Rundong Zuo, Alejandro Alvarez 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). SWAN-SF: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/dataverse-ebcfkm

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

Free to reuse for non-commercial purposes with attribution (CC BY-NC 4.0).