---
title: "keras-rl/keras-rl: papers citing this GitHub repository"
description: "6 papers in the tracked journals link to the GitHub repository keras-rl/keras-rl in their Crossref records, the first in 2020; most of them (2) in 2022."
url: https://scholar4ai.com/code/github-keras-rl-keras-rl
markdown_url: https://scholar4ai.com/code/github-keras-rl-keras-rl.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "6 papers in the tracked journals link to the GitHub repository keras-rl/keras-rl in their Crossref records, the first in 2020; most of them (2) in 2022. (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)
---

# keras-rl/keras-rl: papers linking to it

Research papers in the 480 tracked journals that link to keras-rl/keras-rl (https://github.com/keras-rl/keras-rl), 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
- 5,548 stars
- 1,337 forks
- Python
- license MIT
- created 2016
- https://github.com/keras-rl/keras-rl

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

## Key findings

- 6 papers in the tracked journals link to the GitHub repository keras-rl/keras-rl in their Crossref records, the first in 2020; most of them (2) in 2022.
- By category: AI (6); the journals with the most are Applied Intelligence (3), Expert Systems with Applications (1) and Artificial Intelligence Review (1).

## By year

*Papers linking to keras-rl/keras-rl by publication year*

| Year | Papers |
|---|---:|
| 2020 | 2 |
| 2021 | 1 |
| 2022 | 2 |
| 2024 | 1 |

## Journals

*Journals whose papers link to keras-rl/keras-rl most*

| Journal | Papers |
|---|---:|
| [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 3 |
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 1 |
| [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 1 |
| [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | 1 |

## Papers

*Papers linking to keras-rl/keras-rl, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2020-08-09 | [Multi-DQN: An ensemble of Deep Q-learning agents for stock market forecasting](https://doi.org/10.1016/j.eswa.2020.113820) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Salvatore Carta, Anselmo Ferreira, Alessandro Sebastian Podda et al. | 227 | cites it |
| 2020-09-07 | [A multi-layer and multi-ensemble stock trader using deep learning and deep reinforcement learning](https://doi.org/10.1007/s10489-020-01839-5) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Salvatore Carta, Andrea Corriga, Anselmo Ferreira et al. | 136 | cites it |
| 2022-07-02 | [A survey on deep reinforcement learning for audio-based applications](https://doi.org/10.1007/s10462-022-10224-2) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | Siddique Latif, Heriberto Cuayáhuitl, Farrukh Pervez et al. | 106 | cites it |
| 2021-07-07 | [Air Learning: a deep reinforcement learning gym for autonomous aerial robot visual navigation](https://doi.org/10.1007/s10994-021-06006-6) | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | Srivatsan Krishnan, Behzad Boroujerdian, William Fu et al. | 50 | cites it |
| 2024-06-26 | [LExCI: A framework for reinforcement learning with embedded systems](https://doi.org/10.1007/s10489-024-05573-0) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Kevin Badalian, Lucas Koch, Tobias Brinkmann et al. | 10 | cites it |
| 2022-05-19 | [Towards designing a generic and comprehensive deep reinforcement learning framework](https://doi.org/10.1007/s10489-022-03550-z) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Ngoc Duy Nguyen, Thanh Thi Nguyen, Nhat Truong Pham et al. | 7 | 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). keras-rl/keras-rl: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-keras-rl-keras-rl

```bibtex
@misc{scholar4ai-code-github-keras-rl-keras-rl,
  author = {{Scholar4AI}},
  title = {keras-rl/keras-rl: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-keras-rl-keras-rl}},
  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/).