Scholar4AI Updated 2026-11-03 14:43 UTC+09:00

keras (R package): papers linking to it

CRAN · CRAN.R-project.org/package=keras

← Code and data repositories cited in research papers

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

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Key findings#

  • 17 papers in the tracked journals link to keras (R package) in their Crossref records, the first in 2019; most of them (4) in 2022.
  • By category: Finance (6), Statistics (5) and AI (4); the journals with the most are European Actuarial Journal (6), Neural Computing and Applications (3) and Business & Information Systems Engineering (1).
  • 6 of the papers build on one another: a later paper cites an earlier one that also links keras (R package).

By year#

2019: 1 paper2021: 4 papers2022: 4 papers2023: 2 papers2024: 3 papers2025: 3 papers
20192025
Papers linking to keras (R package) by publication year
YearPapers
20191
20214
20224
20232
20243
20253

Journals#

Journals whose papers link to keras (R package) most
JournalPapers
European Actuarial Journal6
Neural Computing and Applications3
Business & Information Systems Engineering1
Computational Statistics1
Journal of Statistical Theory and Practice1

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Papers linking to keras (R package), most cited first
PublishedTitleJournalAuthorsCitationsLink
2021-03-10Benchmarking Energy Quantification Methods to Predict Heating Energy Performance of Residential Buildings in GermanyBusiness & Information Systems EngineeringSimon Wenninger, Christian Wiethe47cites it
2022-04-02Efficient use of data for LSTM mortality forecastingEuropean Actuarial JournalMathias Lindholm, Lina Palmborg31cites it
2022-04-01Predicting reactions to anomalies in stock movements using a feed-forward deep learning networkInternational Journal of Information Management Data InsightsTalal Alsulaiman21cites it
2023-11-08A multi-task network approach for calculating discrimination-free insurance pricesEuropean Actuarial JournalMathias Lindholm, Ronald Richman, Andreas Tsanakas et al.14cites it
2021-01-29Deep neural networks architecture driven by problem-specific informationNeural Computing and ApplicationsDaniel Urda, Francisco J. Veredas, Javier González-Enrique et al.12cites it
2022-05-12Micro-level prediction of outstanding claim counts based on novel mixture models and neural networksEuropean Actuarial JournalAxel Bücher, Alexander Rosenstock12cites it
2024-03-06A neural network approach for the mortality analysis of multiple populations: a case study on data of the Italian populationEuropean Actuarial JournalMaximilian Euthum, Matthias A. Scherer, Francesco Ungolo9cites it
2019-06-22Recognising innovative companies by using a diversified stacked generalisation method for website classificationApplied IntelligenceMarcin Mirończuk, Jarosław Protasiewicz7cites it
2025-02-15The credibility transformerEuropean Actuarial JournalRonald Richman, Salvatore Scognamiglio, Mario V. Wüthrich7cites it
2021-09-11tofee-tree: automatic feature engineering framework for modeling trend-cycle in time series forecastingNeural Computing and ApplicationsSanthosh Kumar Selvam, Chandrasekharan Rajendran5cites it
2024-02-25High-cardinality categorical covariates in network regressionsJapanese Journal of Statistics and Data ScienceRonald Richman, Mario V. Wüthrich5cites it
2022-12-22EmulART: Emulating radiative transfer—a pilot study on autoencoder-based dimensionality reduction for radiative transfer modelsNeural Computing and ApplicationsJoão Rino-Silvestre, Santiago González-Gaitán, Marko Stalevski et al.4cites it
2025-01-13Time series forecasting via integrating a filtering method: an application to electricity consumptionComputational StatisticsFelipe Leite Coelho da Silva, Josiane da Silva Cordeiro, Kleyton da Costa et al.4cites it
2021-05-25On Ensembles, I-Optimality, and Active LearningJournal of Statistical Theory and PracticeWilliam D. Heavlin2cites it
2023-04-25Learning CHARME models with neural networksStatistical PapersJosé G. Gómez-García, Jalal M. Fadili, Christophe Chesneau0cites it
2024-04-24Combined modelling of micro-level outstanding claim counts and individual claim frequencies in non-life insuranceEuropean Actuarial JournalAxel Bücher, Alexander Rosenstock0cites it
2025-07-20DeepJAM: Joint alignment of multivariate quasi-periodic functional data using deep learningStatistics and ComputingVi Thanh Pham, Jonas Bille Nielsen, Klaus Fuglsang Kofoed et al.0cites 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). keras (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-keras

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

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