ikostrikov/pytorch-a2c-ppo-acktr-gail: papers linking to it

GitHub · 3,909 stars · 840 forks · Python · license MIT · created 2017 · github.com/ikostrikov/pytorch-a2c-ppo-acktr-gail

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to ikostrikov/pytorch-a2c-ppo-acktr-gail (https://github.com/ikostrikov/pytorch-a2c-ppo-acktr-gail), 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 ikostrikov/pytorch-a2c-ppo-acktr-gail in their Crossref records, the first in 2021; most of them (1) in 2025.
By category: AI (3); the journals with the most are Nature Machine Intelligence (1), Machine Learning (1) and International Journal of Computer Vision (1).

By year#

20212025

Papers linking to ikostrikov/pytorch-a2c-ppo-acktr-gail by publication year
Year	Papers
2021	1
2023	1
2025	1

Journals#

Journals whose papers link to ikostrikov/pytorch-a2c-ppo-acktr-gail most
Journal	Papers
Nature Machine Intelligence	1
Machine Learning	1
International Journal of Computer Vision	1

Papers linking to ikostrikov/pytorch-a2c-ppo-acktr-gail, most cited first
Published	Title	Journal	Authors	Citations	Link
2021-02-27	An Exploration of Embodied Visual Exploration	International Journal of Computer Vision	Santhosh Kumar Ramakrishnan, Dinesh Jayaraman, Kristen Lorraine Grauman	102	cites it
2023-01-25	Emergent behaviour and neural dynamics in artificial agents tracking odour plumes	Nature Machine Intelligence	Satpreet H. Singh, Floris van Breugel, Rajesh P. N. Rao et al.	61	cites it
2025-07-13	Perfect counterfactuals in imperfect worlds: modelling noisy implementation of actions in sequential algorithmic recourse	Machine Learning	Yueqing Xuan, Kacper Sokol, Mark Sanderson 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). ikostrikov/pytorch-a2c-ppo-acktr-gail: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-ikostrikov-pytorch-a2c-ppo-acktr-gail

@misc{scholar4ai-code-github-ikostrikov-pytorch-a2c-ppo-acktr-gail,
  author = {{Scholar4AI}},
  title = {ikostrikov/pytorch-a2c-ppo-acktr-gail: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-ikostrikov-pytorch-a2c-ppo-acktr-gail}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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