baosenguo/Kaggle-MoA-2nd-Place-Solution: papers linking to it

GitHub · 170 stars · 36 forks · Jupyter Notebook · created 2020 · github.com/baosenguo/Kaggle-MoA-2nd-Place-Solution

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to baosenguo/Kaggle-MoA-2nd-Place-Solution (https://github.com/baosenguo/Kaggle-MoA-2nd-Place-Solution), 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 the GitHub repository baosenguo/Kaggle-MoA-2nd-Place-Solution in their Crossref records, the first in 2025; most of them (2) in 2025.
By category: AI (3); the journals with the most are Neural Computing and Applications (2) and Machine Learning (1).

By year#

20252026

Papers linking to baosenguo/Kaggle-MoA-2nd-Place-Solution by publication year
Year	Papers
2025	2
2026	1

Journals#

Journals whose papers link to baosenguo/Kaggle-MoA-2nd-Place-Solution most
Journal	Papers
Neural Computing and Applications	2
Machine Learning	1

Papers linking to baosenguo/Kaggle-MoA-2nd-Place-Solution, most cited first
Published	Title	Journal	Authors	Citations	Link
2025-01-01	A survey on self-supervised learning for non-sequential tabular data	Machine Learning	Wei‐Yao Wang, Weiwei Du, Derek Xu et al.	23	cites it
2025-09-24	CorrBoost: a feature selection technique and utility of tabular deep neural networks in software fault prediction	Neural Computing and Applications	Tamanna Sharma, Sanjay Misra, Ricardo Colomo‐Palacios	3	cites it
2026-05-29	Enhanced android malware classification using multi machine learning models and generative adversarial network	Neural Computing and Applications	Nguyen Tan Cam, Nguyen Cong Danh, Nghi Hoang Khoa	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). baosenguo/Kaggle-MoA-2nd-Place-Solution: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-baosenguo-kaggle-moa-2nd-place-solution

@misc{scholar4ai-code-github-baosenguo-kaggle-moa-2nd-place-solution,
  author = {{Scholar4AI}},
  title = {baosenguo/Kaggle-MoA-2nd-Place-Solution: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-baosenguo-kaggle-moa-2nd-place-solution}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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