meta-pytorch/captum: papers linking to it

GitHub · 5,719 stars · 573 forks · Python · license BSD-3-Clause · created 2019 · github.com/meta-pytorch/captum

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to meta-pytorch/captum (https://github.com/meta-pytorch/captum), 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 meta-pytorch/captum in their Crossref records, the first in 2020; most of them (1) in 2024.
By category: AI (2) and Information Systems (1); the journals with the most are Electronic Markets (1), Knowledge-Based Systems (1) and Nature Machine Intelligence (1).

By year#

20202024

Papers linking to meta-pytorch/captum by publication year
Year	Papers
2020	1
2021	1
2024	1

Journals#

Journals whose papers link to meta-pytorch/captum most
Journal	Papers
Electronic Markets	1
Knowledge-Based Systems	1
Nature Machine Intelligence	1

Papers linking to meta-pytorch/captum, most cited first
Published	Title	Journal	Authors	Citations	Link
2020-10-13	Drug discovery with explainable artificial intelligence	Nature Machine Intelligence	José Jiménez-Luna, Francesca Grisoni, Gisbert Schneider	1,061	cites it
2021-04-20	Machine learning in information systems - a bibliographic review and open research issues	Electronic Markets	Benjamin M. Abdel-Karim, Nicolas Pfeuffer, Oliver Fast Hinz	43	cites it
2024-12-18	Classification of cognitive syndromes in a Southeast Asian population: Interpretable graph convolutional neural networks	Knowledge-Based Systems	Charlene Z. L. Ong, Ashwati Vipin, Yi Jin Leow et al.	1	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). meta-pytorch/captum: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-meta-pytorch-captum

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

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