memory-profiler (Python package): papers linking to it

PyPI · pypi.org/project/memory-profiler/

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to memory-profiler (Python package) (https://pypi.org/project/memory-profiler/), 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 memory-profiler (Python package) in their Crossref records, the first in 2020; most of them (2) in 2025.
By category: AI (2) and Information Systems (1); the journals with the most are Neural Computing and Applications (1), Information Processing & Management (1) and Information Systems Frontiers (1).

By year#

20202025

Papers linking to memory-profiler (Python package) by publication year
Year	Papers
2020	1
2025	2

Journals#

Journals whose papers link to memory-profiler (Python package) most
Journal	Papers
Neural Computing and Applications	1
Information Processing & Management	1
Information Systems Frontiers	1

Papers linking to memory-profiler (Python package), most cited first
Published	Title	Journal	Authors	Citations	Link
2020-10-06	Detecting health misinformation in online health communities: Incorporating behavioral features into machine learning based approaches	Information Processing & Management	Yuehua Zhao, Jingwei Da, Jiaqi Yan	191	cites it
2025-01-24	CTMBIDS: convolutional Tsetlin machine-based intrusion detection system for DDoS attacks in an SDN environment	Neural Computing and Applications	Rasoul Jafari Gohari, Laya Aliahmadipour, Marjan Kuchaki Rafsanjani	15	cites it
2025-06-05	5G Native Network Function for False Base Station Detection Using Machine Learning Technique	Information Systems Frontiers	Hoonyong Park, Philip Virgil Astillo, Taeguen Kim 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). memory-profiler (Python package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/pypi-memory-profiler

@misc{scholar4ai-code-pypi-memory-profiler,
  author = {{Scholar4AI}},
  title = {memory-profiler (Python package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/pypi-memory-profiler}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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