google-deepmind/dsprites-dataset: papers linking to it

GitHub · 541 stars · 69 forks · Jupyter Notebook · license Apache-2.0 · created 2017 · github.com/google-deepmind/dsprites-dataset

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Research papers in the 480 tracked journals that link to google-deepmind/dsprites-dataset (https://github.com/google-deepmind/dsprites-dataset), 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#

13 papers in the tracked journals link to the GitHub repository google-deepmind/dsprites-dataset in their Crossref records, the first in 2019; most of them (3) in 2025.
By category: AI (13); the journals with the most are Machine Learning (3), International Journal of Computer Vision (3) and Pattern Recognition (2).

By year#

20192026

Papers linking to google-deepmind/dsprites-dataset by publication year
Year	Papers
2019	1
2020	1
2022	3
2023	1
2024	3
2025	3
2026	1

Journals#

Journals whose papers link to google-deepmind/dsprites-dataset most
Journal	Papers
Machine Learning	3
International Journal of Computer Vision	3
Pattern Recognition	2
Nature Machine Intelligence	1
Knowledge-Based Systems	1

Papers linking to google-deepmind/dsprites-dataset, most cited first
Published	Title	Journal	Authors	Citations	Link
2019-10-23	Augmented Autoencoders: Implicit 3D Orientation Learning for 6D Object Detection	International Journal of Computer Vision	Martin Sundermeyer, Zoltán-Csaba Márton, Maximilian Durner et al.	139	cites it
2023-11-29	Explainable reinforcement learning (XRL): a systematic literature review and taxonomy	Machine Learning	Yanzhe Bekkemoen	54	cites it
2020-08-07	Attribute-based regularization of latent spaces for variational auto-encoders	Neural Computing and Applications	Ashis Kumar Pati, Alexander Lerch	44	cites it
2026-06-01	Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models: A Survey and Benchmark	International Journal of Computer Vision	Yi Xin, Jianjiang Yang, Siqi Luo et al.	28	cites it
2022-07-21	SSDMM-VAE: variational multi-modal disentangled representation learning	Applied Intelligence	Arnab Kumar Mondal, Ajay Sailopal, Parag Singla et al.	8	cites it
2024-04-30	Improving disentanglement in variational auto-encoders via feature imbalance-informed dimension weighting	Knowledge-Based Systems	Yue Liu, Zhenyao Yu, Zitu Liu et al.	7	cites it
2025-02-06	Discovering fully semantic representations via centroid- and orientation-aware feature learning	Nature Machine Intelligence	Jaehoon Cha, Jinhae Park, Samuel Pinilla et al.	6	cites it
2024-01-06	Benchmarking and Analysis of Unsupervised Object Segmentation from Real-World Single Images	International Journal of Computer Vision	Yafei Yang, Bo Yang	3	cites it
2024-08-30	A Novel Multimodal Generative Learning Model based on Basic Fuzzy Concepts	Cognitive Computation	Huankun Sheng, Hongwei Mo, Tengteng Zhang	2	cites it
2025-10-24	DualAdaptNet: Enhancing domain adaptation regression with error accumulation reduction and dual-head heterogeneous learning	Pattern Recognition	Xin Wang, Yuan Wu, Xingyu Zhu et al.	2	cites it
2025-08-19	Toward practical human-interpretable explanations	Machine Learning	Alon Malach, Amiel Meiseles, Ron Bitton et al.	1	cites it
2022-03-29	DEFT: distilling entangled factors by preventing information diffusion	Machine Learning	Jiantao, Lin Wang, Bo Yang et al.	0	cites it
2022-09-22	Disentangling the correlated continuous and discrete generative factors of data	Pattern Recognition	Jaewoong Choi, Geonho Hwang, Myungjoo Kang	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). google-deepmind/dsprites-dataset: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-google-deepmind-dsprites-dataset

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

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