hydra-ecosystem/hydra: papers linking to it

GitHub · 10,731 stars · 1,003 forks · Python · license MIT · created 2019 · github.com/hydra-ecosystem/hydra

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to hydra-ecosystem/hydra (https://github.com/hydra-ecosystem/hydra), 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#

4 papers in the tracked journals link to the GitHub repository hydra-ecosystem/hydra in their Crossref records, the first in 2023; most of them (3) in 2025.
By category: AI (4); the journals with the most are Machine Learning (1), Knowledge and Information Systems (1) and Nature Machine Intelligence (1).

By year#

20232025

Papers linking to hydra-ecosystem/hydra by publication year
Year	Papers
2023	1
2025	3

Journals#

Journals whose papers link to hydra-ecosystem/hydra most
Journal	Papers
Machine Learning	1
Knowledge and Information Systems	1
Nature Machine Intelligence	1
Knowledge-Based Systems	1

Papers linking to hydra-ecosystem/hydra, most cited first
Published	Title	Journal	Authors	Citations	Link
2023-10-19	Mitigating the missing-fragmentation problem in de novo peptide sequencing with a two-stage graph-based deep learning model	Nature Machine Intelligence	Zeping Mao, Ruixue Zhang, Lei Xin et al.	42	cites it
2025-02-24	Deep Errors-in-Variables using a diffusion model	Machine Learning	Josua Faller, Jörg Martin, Clemens Elster	2	cites it
2025-07-21	CoSTI: Consistency models for (a faster) spatio-temporal imputation	Knowledge-Based Systems	Javier Solís-García, Belén Vega-Márquez, Juan A. Nepomuceno et al.	2	cites it
2025-08-28	Focal Sampling: SGD biased towards early important samples for efficient image classification with augmentation selection	Knowledge and Information Systems	Alessio Quercia, Fernanda Nader, Abigail Morrison 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). hydra-ecosystem/hydra: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-hydra-ecosystem-hydra

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

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