---
title: "timeseriesAI/tsai: papers citing this GitHub repository"
description: "4 papers in the tracked journals link to the GitHub repository timeseriesAI/tsai in their Crossref records, the first in 2023; most of them (2) in 2025."
url: https://scholar4ai.com/code/github-timeseriesai-tsai
markdown_url: https://scholar4ai.com/code/github-timeseriesai-tsai.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "4 papers in the tracked journals link to the GitHub repository timeseriesAI/tsai in their Crossref records, the first in 2023; most of them (2) in 2025. (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)
---

# timeseriesAI/tsai: papers linking to it

Research papers in the 480 tracked journals that link to timeseriesAI/tsai (https://github.com/timeseriesAI/tsai), 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
- 6,140 stars
- 720 forks
- Jupyter Notebook
- license Apache-2.0
- created 2019
- https://github.com/timeseriesAI/tsai

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

## Key findings

- 4 papers in the tracked journals link to the GitHub repository timeseriesAI/tsai in their Crossref records, the first in 2023; most of them (2) in 2025.
- By category: AI (4); the journals with the most are Applied Intelligence (1), Neural Computing and Applications (1) and Cognitive Computation (1).

## By year

*Papers linking to timeseriesAI/tsai by publication year*

| Year | Papers |
|---|---:|
| 2023 | 1 |
| 2024 | 1 |
| 2025 | 2 |

## Journals

*Journals whose papers link to timeseriesAI/tsai most*

| Journal | Papers |
|---|---:|
| [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 1 |
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 1 |
| [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | 1 |
| [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | 1 |

## Papers

*Papers linking to timeseriesAI/tsai, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2023-06-02 | [Artificial intelligence for improving Nitrogen Dioxide forecasting of Abu Dhabi environment agency ground-based stations](https://doi.org/10.1186/s40537-023-00754-z) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | Aamna Al Shehhi, Roy E. Welsch | 18 | cites it |
| 2024-12-16 | [On the Integration of Large-Scale Time Series Distance Matrices Into Deep Visual Analytic Tools](https://doi.org/10.1007/s12559-024-10394-x) | [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | Inmaculada Santamaria-Valenzuela, Víctor Rodríguez-Fernández, David Camacho | 1 | cites it |
| 2025-02-26 | [Predicting hemodynamic parameters based on arterial blood pressure waveform using self-supervised learning and fine-tuning](https://doi.org/10.1007/s10489-025-06391-8) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Ke Liao, Armağan Elibol, Ziyan Gao et al. | 1 | cites it |
| 2025-08-02 | [Surfing the Bitcoin waves: comprehensive trend forecasting with various trader types](https://doi.org/10.1007/s00521-025-11496-9) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Can Ali Ateş, Emre Çoban, Tuğba Gürgen Erdoğan | 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). timeseriesAI/tsai: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-timeseriesai-tsai

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