SheffieldML/GPyOpt: papers linking to it

GitHub · 943 stars · 258 forks · Jupyter Notebook · license BSD-3-Clause · created 2014 · archived · github.com/SheffieldML/GPyOpt

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to SheffieldML/GPyOpt (https://github.com/SheffieldML/GPyOpt), 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#

6 papers in the tracked journals link to the GitHub repository SheffieldML/GPyOpt in their Crossref records, the first in 2019; most of them (2) in 2025.
By category: Operations Research (5) and AI (1); the journals with the most are Computational Optimization and Applications (2), Journal of Optimization Theory and Applications (1) and Computers & Industrial Engineering (1).
2 of the papers build on one another: a later paper cites an earlier one that also links SheffieldML/GPyOpt.

By year#

20192025

Papers linking to SheffieldML/GPyOpt by publication year
Year	Papers
2019	1
2020	1
2021	1
2022	1
2025	2

Journals#

Journals whose papers link to SheffieldML/GPyOpt most
Journal	Papers
Computational Optimization and Applications	2
Journal of Optimization Theory and Applications	1
Computers & Industrial Engineering	1
Optimization and Engineering	1
Expert Systems with Applications	1

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.

Global optimization via inverse distance weighting and radial basis functions Computational Optimization and Applications, 2020
- Global and Preference-Based Optimization with Mixed Variables Using Piecewise Affine Surrogates Journal of Optimization Theory and Applications, 2025 — cites the paper above

Papers linking to SheffieldML/GPyOpt, most cited first
Published	Title	Journal	Authors	Citations	Link
2019-08-20	Continuous control with Stacked Deep Dynamic Recurrent Reinforcement Learning for portfolio optimization	Expert Systems with Applications	Amine Mohamed Aboussalah, Chi-Guhn Lee	110	cites it
2020-07-27	Global optimization via inverse distance weighting and radial basis functions	Computational Optimization and Applications	Alberto Bemporad	69	cites it
2021-04-20	Bayesian optimization for a multiple-component system with target values	Computers & Industrial Engineering	Jihwan Jeong, Hayong Shin	7	cites it
2025-01-08	Global and Preference-Based Optimization with Mixed Variables Using Piecewise Affine Surrogates	Journal of Optimization Theory and Applications	Mengjia Zhu, Alberto Bemporad	5	cites it
2025-12-26	A derivative-free approach to mixed integer constrained multiobjective nonsmooth black-box optimization	Computational Optimization and Applications	Giampaolo Liuzzi, Stefano Lucidi	1	cites it
2022-01-13	A novel optimization perspective to the problem of designing sequences of tasks in a reinforcement learning framework	Optimization and Engineering	Ruggiero Seccia, Francesco Foglino, Matteo Leonetti 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). SheffieldML/GPyOpt: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-sheffieldml-gpyopt

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

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