lessw2020/Ranger-Deep-Learning-Optimizer: papers linking to it

GitHub · 1,207 stars · 176 forks · Python · license Apache-2.0 · created 2019 · github.com/lessw2020/Ranger-Deep-Learning-Optimizer

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to lessw2020/Ranger-Deep-Learning-Optimizer (https://github.com/lessw2020/Ranger-Deep-Learning-Optimizer), 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#

4 papers in the tracked journals link to the GitHub repository lessw2020/Ranger-Deep-Learning-Optimizer in their Crossref records, the first in 2022; most of them (2) in 2025.
By category: Operations Research (2), Economics (1) and AI (1); the journals with the most are Computational Economics (1), Mathematical Programming Computation (1) and Applied Intelligence (1).

By year#

20222025

Papers linking to lessw2020/Ranger-Deep-Learning-Optimizer by publication year
Year	Papers
2022	1
2023	1
2025	2

Journals#

Journals whose papers link to lessw2020/Ranger-Deep-Learning-Optimizer most
Journal	Papers
Computational Economics	1
Mathematical Programming Computation	1
Applied Intelligence	1
Journal of Global Optimization	1

Papers linking to lessw2020/Ranger-Deep-Learning-Optimizer, most cited first
Published	Title	Journal	Authors	Citations	Link
2023-09-22	N-BEATS Perceiver: A Novel Approach for Robust Cryptocurrency Portfolio Forecasting	Computational Economics	Attilio Sbrana, Paulo André Lima de Castro	16	cites it
2022-09-23	Deep structural enhanced network for document clustering	Applied Intelligence	Lina Ren, Yongbin Qin, Yanping Chen et al.	8	cites it
2025-02-13	CDOpt: a Python package for a class of Riemannian optimization	Mathematical Programming Computation	Nachuan Xiao, Xiaoyin Hu, Xin Liu et al.	1	cites it
2025-07-16	A theoretical and empirical study of new adaptive algorithms with additional momentum steps and shifted updates for stochastic non-convex optimization	Journal of Global Optimization	Cristian Daniel Alecsa	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). lessw2020/Ranger-Deep-Learning-Optimizer: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-lessw2020-ranger-deep-learning-optimizer

@misc{scholar4ai-code-github-lessw2020-ranger-deep-learning-optimizer,
  author = {{Scholar4AI}},
  title = {lessw2020/Ranger-Deep-Learning-Optimizer: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-lessw2020-ranger-deep-learning-optimizer}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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