---
title: "xgboost (R package): papers citing this CRAN package"
description: "27 papers in the tracked journals link to xgboost (R package) in their Crossref records, the first in 2018; most of them (11) in 2024."
url: https://scholar4ai.com/code/cran-xgboost
markdown_url: https://scholar4ai.com/code/cran-xgboost.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "27 papers in the tracked journals link to xgboost (R package) in their Crossref records, the first in 2018; most of them (11) in 2024. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# xgboost (R package): papers linking to it

Research papers in the 480 tracked journals that link to xgboost (R package) (https://CRAN.R-project.org/package=xgboost), 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.

- CRAN
- https://CRAN.R-project.org/package=xgboost

All repositories: https://scholar4ai.com/code.md

## Key findings

- 27 papers in the tracked journals link to xgboost (R package) in their Crossref records, the first in 2018; most of them (11) in 2024.
- By category: AI (14), Economics (3) and Operations Research (3); the journals with the most are IEEE Transactions on Neural Networks and Learning Systems (3), IEEE Transactions on Knowledge and Data Engineering (3) and Neural Computing and Applications (2).

## By year

*Papers linking to xgboost (R package) by publication year*

| Year | Papers |
|---|---:|
| 2018 | 1 |
| 2019 | 1 |
| 2020 | 2 |
| 2021 | 3 |
| 2022 | 1 |
| 2023 | 3 |
| 2024 | 11 |
| 2025 | 3 |
| 2026 | 2 |

## Journals

*Journals whose papers link to xgboost (R package) most*

| Journal | Papers |
|---|---:|
| [IEEE Transactions on Neural Networks and Learning Systems](https://scholar4ai.com/journals/ieee-transactions-on-neural-networks-and-learning-systems.md) | 3 |
| [IEEE Transactions on Knowledge and Data Engineering](https://scholar4ai.com/journals/ieee-transactions-on-knowledge-and-data-engineering.md) | 3 |
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 2 |
| [Health Care Management Science](https://scholar4ai.com/journals/health-care-management-science.md) | 2 |
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 2 |

## Papers

*Papers linking to xgboost (R package), most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2020-07-06 | [Super ensemble learning for daily streamflow forecasting: large-scale demonstration and comparison with multiple machine learning algorithms](https://doi.org/10.1007/s00521-020-05172-3) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Hristos Tyralis, Georgia Papacharalampous, Andreas Langousis | 177 | cites it |
| 2018-08-07 | [Incorporating domain knowledge in machine learning for soccer outcome prediction](https://doi.org/10.1007/s10994-018-5747-8) | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | Daniel Berrar, Philippe Lopes, Werner Dubitzky | 91 | cites it |
| 2021-01-06 | [Predicting Firm-Level Bankruptcy in the Spanish Economy Using Extreme Gradient Boosting](https://doi.org/10.1007/s10614-020-10078-2) | [Computational Economics](https://scholar4ai.com/journals/computational-economics.md) | Matthew Smith, Francisco Álvarez | 52 | cites it |
| 2023-09-28 | [An integrated approach of ensemble learning methods for stock index prediction using investor sentiments](https://doi.org/10.1016/j.eswa.2023.121710) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Shangkun Deng, Yingke Zhu, Yiting Yu et al. | 52 | cites it |
| 2021-03-10 | [Benchmarking Energy Quantification Methods to Predict Heating Energy Performance of Residential Buildings in Germany](https://doi.org/10.1007/s12599-021-00691-2) | [Business & Information Systems Engineering](https://scholar4ai.com/journals/business-information-systems-engineering.md) | Simon Wenninger, Christian Wiethe | 47 | cites it |
| 2023-03-13 | [Predicting drug shortages using pharmacy data and machine learning](https://doi.org/10.1007/s10729-022-09627-y) | [Health Care Management Science](https://scholar4ai.com/journals/health-care-management-science.md) | Raman Pall, Yvan Gauthier, Sofia Auer et al. | 44 | cites it |
| 2024-02-14 | [Meta-MolNet: A Cross-Domain Benchmark for Few Examples Drug Discovery](https://doi.org/10.1109/tnnls.2024.3359657) | [IEEE Transactions on Neural Networks and Learning Systems](https://scholar4ai.com/journals/ieee-transactions-on-neural-networks-and-learning-systems.md) | Qiujie Lv, Guanxing Chen, Ziduo Yang et al. | 39 | cites it |
| 2024-01-13 | [A framework to improve churn prediction performance in retail banking](https://doi.org/10.1186/s40854-023-00558-3) | [Financial Innovation](https://scholar4ai.com/journals/financial-innovation.md) | João B. G. Brito, Guilherme Brandelli Bucco, Rodrigo Heldt et al. | 35 | cites it |
| 2020-07-06 | [Machine learning for total cloud cover prediction](https://doi.org/10.1007/s00521-020-05139-4) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Ágnes Baran, Sebastian Lerch, Mehrez El Ayari et al. | 34 | cites it |
| 2024-01-23 | [Consumers’ ambiguous perceptions of advertising disclosures in influencer marketing: Disentangling the effects on current and future social media engagement](https://doi.org/10.1007/s12525-023-00679-8) | [Electronic Markets](https://scholar4ai.com/journals/electronic-markets.md) | Adrian Waltenrath | 31 | cites it |
| 2023-01-30 | [Adaptive solution prediction for combinatorial optimization](https://doi.org/10.1016/j.ejor.2023.01.054) | [European Journal of Operational Research](https://scholar4ai.com/journals/european-journal-of-operational-research.md) | Yunzhuang Shen, Yuan Sun, Xiaodong Li et al. | 13 | cites it |
| 2025-08-04 | [From point to probabilistic gradient boosting for claim frequency and severity prediction](https://doi.org/10.1007/s13385-025-00428-5) | [European Actuarial Journal](https://scholar4ai.com/journals/european-actuarial-journal.md) | Dominik Chevalier, Marie‐Pier Côté | 13 | cites it |
| 2024-07-03 | [Prediction-led prescription: Optimal Decision-Making in times of turbulence and business performance improvement](https://doi.org/10.1016/j.jbusres.2024.114805) | [Journal of Business Research](https://scholar4ai.com/journals/journal-of-business-research.md) | Andreas Schäfers, Vasileios Bougioukos, Georgios Karamatzanis et al. | 11 | cites it |
| 2024-07-02 | [StackAMP: Stacking-Based Ensemble Classifier for Antimicrobial Peptide Identification](https://doi.org/10.1109/tai.2024.3421176) | [IEEE Transactions on Artificial Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-artificial-intelligence.md) | Tasmin Karim, Md. Shazzad Hossain Shaon, Md. Mamun Ali et al. | 10 | cites it |
| 2024-08-15 | [A nowcasting model of industrial production using alternative data and machine learning approaches](https://doi.org/10.1016/j.japwor.2024.101271) | [Japan and the World Economy](https://scholar4ai.com/journals/japan-and-the-world-economy.md) | Kakuho Furukawa, Ryohei Hisano, Yukio Minoura et al. | 10 | cites it |
| 2021-01-12 | [Technology Integration and Analysis Using Boosting and Ensemble](https://doi.org/10.3390/joitmc7010027) | [Journal of Open Innovation Technology Market and Complexity](https://scholar4ai.com/journals/journal-of-open-innovation-technology-market-and-complexity.md) | Sunghae Jun | 8 | cites it |
| 2024-01-19 | [Heterogeneity of national accounting systems, world-class universities and financial resources: What are the links?](https://doi.org/10.1016/j.joi.2024.101502) | [Journal of Informetrics](https://scholar4ai.com/journals/journal-of-informetrics.md) | Alessandro Avenali, Cinzia C. Daraio, Simone Di Leo et al. | 8 | cites it |
| 2024-04-01 | [Bootstrapping on Continuous-Time Dynamic Graphs for Crowd Flow Modeling](https://doi.org/10.1109/tkde.2024.3383663) | [IEEE Transactions on Knowledge and Data Engineering](https://scholar4ai.com/journals/ieee-transactions-on-knowledge-and-data-engineering.md) | Yi Xu, Liangzhe Han, Leilei Sun et al. | 8 | cites it |
| 2019-06-22 | [Recognising innovative companies by using a diversified stacked generalisation method for website classification](https://doi.org/10.1007/s10489-019-01509-1) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Marcin Mirończuk, Jarosław Protasiewicz | 7 | cites it |
| 2022-07-27 | [Aiding the prescriber: developing a machine learning approach to personalized risk modeling for chronic opioid therapy amongst US Army soldiers](https://doi.org/10.1007/s10729-022-09605-4) | [Health Care Management Science](https://scholar4ai.com/journals/health-care-management-science.md) | Margrét V. Bjarnadóttir, David Anderson, Ritu Agarwal et al. | 7 | cites it |
| 2024-01-09 | [Machine learning approaches to identify lithium concentration in petroleum produced waters](https://doi.org/10.1007/s13563-023-00409-8) | [Mineral Economics](https://scholar4ai.com/journals/mineral-economics.md) | Emil D. Attanasi, Timothy C. Coburn, Philip A. Freeman | 6 | cites it |
| 2024-01-31 | [Deep Ensemble Transformers for Dimensionality Reduction](https://doi.org/10.1109/tnnls.2024.3357621) | [IEEE Transactions on Neural Networks and Learning Systems](https://scholar4ai.com/journals/ieee-transactions-on-neural-networks-and-learning-systems.md) | Maria Nareklishvili, Marius Geitle | 6 | cites it |
| 2024-11-13 | [Manifoldron: Direct Space Partition via Manifold Discovery](https://doi.org/10.1109/tnnls.2024.3486252) | [IEEE Transactions on Neural Networks and Learning Systems](https://scholar4ai.com/journals/ieee-transactions-on-neural-networks-and-learning-systems.md) | Dayang Wang, Fenglei Fan, Bojian Hou et al. | 6 | cites it |
| 2025-08-22 | [Spindle thermal error modeling with linear and nonlinear hybrid tandem metamodel based on statistical and machine learning approaches](https://doi.org/10.1016/j.eswa.2025.129449) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Menghua Li, Mingchang Chih, Chia-Fu Kou et al. | 2 | cites it |
| 2025-01-24 | [HPST-GT: Full-Link Delivery Time Estimation Via Heterogeneous Periodic Spatial-Temporal Graph Transformer](https://doi.org/10.1109/tkde.2025.3533610) | [IEEE Transactions on Knowledge and Data Engineering](https://scholar4ai.com/journals/ieee-transactions-on-knowledge-and-data-engineering.md) | Shuai Wang, Hai Wang, Li Lin et al. | 1 | cites it |
| 2026-05-12 | [Semi-Supervised Adaptive Fast XGBoost for Multiclass Stream Classification](https://doi.org/10.1109/tkde.2026.3692580) | [IEEE Transactions on Knowledge and Data Engineering](https://scholar4ai.com/journals/ieee-transactions-on-knowledge-and-data-engineering.md) | Deividy Amorim Policarpo, Yuji Yamada Correa, Fabiano Baldo | 0 | cites it |
| 2026-07-27 | [Solving Imbalanced Problems With Multilayer Ensemble Balanced Fuzzy Inference Broad Network](https://doi.org/10.1109/tfuzz.2026.3717303) | [IEEE Transactions on Fuzzy Systems](https://scholar4ai.com/journals/ieee-transactions-on-fuzzy-systems.md) | Wuxing Chen, Zhiwen Yu, Kaixiang Yang et al. | 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). xgboost (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-xgboost

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

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).