favorita-grocery-sales-forecasting: papers linking to it

Kaggle · www.kaggle.com/competitions/favorita-grocery-sales-forecasting

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to favorita-grocery-sales-forecasting (https://www.kaggle.com/competitions/favorita-grocery-sales-forecasting), 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 Kaggle dataset favorita-grocery-sales-forecasting in their Crossref records, the first in 2022; most of them (1) in 2026.
By category: Economics (1), Operations Research (1) and AI (1); the journals with the most are Computational Economics (1), Annals of Operations Research (1) and Machine Learning (1).

By year#

20222026

Papers linking to favorita-grocery-sales-forecasting by publication year
Year	Papers
2022	1
2023	1
2026	1

Journals#

Journals whose papers link to favorita-grocery-sales-forecasting most
Journal	Papers
Computational Economics	1
Annals of Operations Research	1
Machine Learning	1

Papers linking to favorita-grocery-sales-forecasting, most cited first
Published	Title	Journal	Authors	Citations	Link
2022-07-01	Deep-learning model using hybrid adaptive trend estimated series for modelling and forecasting sales	Annals of Operations Research	Md. Iftekharul Alam Efat, Petr Hájek, Mohammad Zoynul Abedin et al.	69	cites it
2023-03-13	SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting	Machine Learning	Rakshitha Godahewa, Geoffrey I. Webb, Daniel Francis Schmidt et al.	15	cites it
2026-09-17	CensoredPatchTST: A Channel-Independent Transformer with Asymmetric Loss for Latent Demand Recovery	Computational Economics	Lan Du, Xiujiao Qin, Hailong Yu	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). favorita-grocery-sales-forecasting: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-competition-favorita-grocery-sales-forecasting

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

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