---
title: "meta-pytorch/captum: papers citing this GitHub repository"
description: "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."
url: https://scholar4ai.com/code/github-meta-pytorch-captum
markdown_url: https://scholar4ai.com/code/github-meta-pytorch-captum.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "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. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# meta-pytorch/captum: papers linking to it

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.

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

All repositories: https://scholar4ai.com/code.md

## 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

*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](https://scholar4ai.com/journals/electronic-markets.md) | 1 |
| [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 1 |
| [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 1 |

## Papers

*Papers linking to meta-pytorch/captum, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2020-10-13 | [Drug discovery with explainable artificial intelligence](https://doi.org/10.1038/s42256-020-00236-4) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 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](https://doi.org/10.1007/s12525-021-00459-2) | [Electronic Markets](https://scholar4ai.com/journals/electronic-markets.md) | 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](https://doi.org/10.1016/j.knosys.2024.112855) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 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

```bibtex
@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}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).