---
title: "numenta/NAB: papers citing this GitHub repository"
description: "5 papers in the tracked journals link to the GitHub repository numenta/NAB in their Crossref records, the first in 2020; most of them (2) in 2023."
url: https://scholar4ai.com/code/github-numenta-nab
markdown_url: https://scholar4ai.com/code/github-numenta-nab.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "5 papers in the tracked journals link to the GitHub repository numenta/NAB in their Crossref records, the first in 2020; most of them (2) in 2023. (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)
---

# numenta/NAB: papers linking to it

Research papers in the 480 tracked journals that link to numenta/NAB (https://github.com/numenta/NAB), 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
- 2,114 stars
- 871 forks
- Jupyter Notebook
- license MIT
- created 2014
- https://github.com/numenta/NAB

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

## Key findings

- 5 papers in the tracked journals link to the GitHub repository numenta/NAB in their Crossref records, the first in 2020; most of them (2) in 2023.
- By category: AI (5); the journals with the most are Artificial Intelligence Review (1), Journal Of Big Data (1) and Applied Intelligence (1).

## By year

*Papers linking to numenta/NAB by publication year*

| Year | Papers |
|---|---:|
| 2020 | 1 |
| 2022 | 2 |
| 2023 | 2 |

## Journals

*Journals whose papers link to numenta/NAB most*

| Journal | Papers |
|---|---:|
| [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 1 |
| [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | 1 |
| [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 1 |
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 1 |
| [Data Mining and Knowledge Discovery](https://scholar4ai.com/journals/data-mining-and-knowledge-discovery.md) | 1 |

## Papers

*Papers linking to numenta/NAB, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2020-02-11 | [Sensor data quality: a systematic review](https://doi.org/10.1186/s40537-020-0285-1) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | Hui Yie Teh, Andreas W. Kempa-Liehr, Kevin I‐Kai Wang | 376 | cites it |
| 2023-06-07 | [A review on big data based on deep neural network approaches](https://doi.org/10.1007/s10462-023-10512-5) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | M Rithani, R Prasanna Kumar, Srinath Doss | 98 | cites it |
| 2023-11-18 | [Navigating the metric maze: a taxonomy of evaluation metrics for anomaly detection in time series](https://doi.org/10.1007/s10618-023-00988-8) | [Data Mining and Knowledge Discovery](https://scholar4ai.com/journals/data-mining-and-knowledge-discovery.md) | Sondre Sørbø, Massimiliano Ruocco | 58 | cites it |
| 2022-08-08 | [Efficient anomaly identification in temporal and non-temporal industrial data using tree based approaches](https://doi.org/10.1007/s10489-022-03940-3) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Jyotirmoy Sarkar, Snehanshu Saha, Santonu Sarkar | 6 | cites it |
| 2022-11-13 | [AREP: an adaptive, machine learning-based algorithm for real-time anomaly detection on network telemetry data](https://doi.org/10.1007/s00521-022-08000-y) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Károly Farkas | 6 | 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). numenta/NAB: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-numenta-nab

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