numenta/NAB: papers linking to it

GitHub · 2,114 stars · 871 forks · Jupyter Notebook · license MIT · created 2014 · github.com/numenta/NAB

← Code and data repositories cited in research papers

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.

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#

20202023

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	1
Journal Of Big Data	1
Applied Intelligence	1
Neural Computing and Applications	1
Data Mining and Knowledge Discovery	1

Papers linking to numenta/NAB, most cited first
Published	Title	Journal	Authors	Citations	Link
2020-02-11	Sensor data quality: a systematic review	Journal Of Big Data	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	Artificial Intelligence Review	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	Data Mining and Knowledge Discovery	Sondre Sørbø, Massimiliano Ruocco	58	cites it
2022-08-08	Efficient anomaly identification in temporal and non-temporal industrial data using tree based approaches	Applied Intelligence	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	Neural Computing and Applications	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

@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}
}

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