Results 1 to 10 of about 1,081,162 (161)
Generating realistic synthetic data [PDF]
International Journal of Population Data ScienceSynthetic data has many different uses such as testing pipelines and training people for using new methods and technologies, which could be used within data linkage.
Zoe White
doaj +2 more sources
The UK Synthetic Data Community Group - The VSTAR Framework for Responsible Synthetic Data [PDF]
International Journal of Population Data ScienceSynthetic data is increasingly recognised as a powerful tool for accelerating research, training, and innovation within Trusted Research Environments (TREs), but its safe and responsible use requires clear governance standards and shared best practices.
Lewis Hotchkiss +9 more
doaj +2 more sources
Synthetic Data, Synthetic Media, and Surveillance
Surveillance & SocietyPublic and scholarly interest in the related concepts of synthetic data and synthetic media has exploded in recent years. From issues raised by the generation of synthetic datasets to train machine learning models to the public-facing, consumer ...
Aaron Martin, Bryce Newell
doaj +2 more sources
Business Information ReviewSynthetic data generated using logistic, linear or exponential relationships with categorical variables with an element of multi-collinearity
Jimmy Nassif, Joe Tekli, Marc Kamradt
+9 more sources
CoRR, 2023 Synthetic data are becoming a critical tool for building artificially intelligent systems. Simulators provide a way of generating data systematically and at scale. These data can then be used either exclusively, or in conjunction with real data, for training and testing systems. Synthetic data are particularly attractive in cases where the availability
Daniel McDuff +2 more
openaire +3 more sources
CoRR, 2023 This study leverages synthetic data as a validation set to reduce overfitting and ease the selection of the best model in AI development. While synthetic data have been used for augmenting the training set, we find that synthetic data can also significantly diversify the validation set, offering marked advantages in domains like healthcare, where data ...
Qixin Hu, Alan L. Yuille, Zongwei Zhou
openaire +2 more sources
Synthetic data, real errors: how (not) to publish and use synthetic data
CoRR, 2023 Proceedings of the 40th International Conference on Machine Learning (ICML 2023)
Boris van Breugel +2 more
openaire +4 more sources
Fake It Till You Make It: Guidelines for Effective Synthetic Data Generation
Applied Sciences, 2021 Synthetic data provides a privacy protecting mechanism for the broad usage and sharing of healthcare data for secondary purposes. It is considered a safe approach for the sharing of sensitive data as it generates an artificial dataset that contains no ...
Fida K. Dankar, Mahmoud Ibrahim
doaj +1 more source
Synthetic data for reef modelling
Ecological Informatics, 2023 Synthetic data mimics the statistical properties of real-world datasets while removing reference to sensitive or confidential information in the original dataset (Quintana, 2020). Synthetic data is also useful for general model testing and development, with many methods available for generating data from machine learning models (Raghunathan, 2021 ...
Rose Crocker +4 more
openaire +2 more sources
Synthetic Data for Model Selection
CoRR, 2021 Recent breakthroughs in synthetic data generation approaches made it possible to produce highly photorealistic images which are hardly distinguishable from real ones. Furthermore, synthetic generation pipelines have the potential to generate an unlimited number of images.
Matan Fintz +4 more
openaire +3 more sources