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A tool for generating synthetic data
Proceedings of the First International Conference on Data Science, E-learning and Information Systems, 2018It is popular to use real-world data to evaluate data mining techniques. However, there are some disadvantages to use real-world data for such purposes. Firstly, real-world data in most domains is difficult to obtain for several reasons, such as budget, technical or ethical.
Taoxin Peng, Alexander Telle
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Bayesian Generation of Synthetic Data
Generation of synthetic data can be a valuable tool for machine-learning tasks and, in general, managing large volumes of data. This paper presents a technique for creating synthetic data through Bayesian Generation, so that synthetic data maintain the original probability distribution and can be exploited for training Machine-Learning models in place ...Fosci, Paolo +3 more
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Taxonomizing Synthetic Data for Law
SSRN Electronic JournalSynthetic data is increasingly important in data usage and AI design, creating novel legal and policy dilemmas. All too often, discussions of synthetic data treat it as entirely distinct from “real,” collected data, overlooking the risks posed by different kinds and uses of synthetic data.
Cofone, I, Strandburg, KJ, Tilmes, N
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Visual Perception with Synthetic Data
2020In recent years, learning-based methods have become the dominant approach to solving computer vision tasks. A major reason for this development is their automatic adaptation to the particularities of the task at hand by learning a model of the problem from (training) data.
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Engineering living therapeutics with synthetic biology
Nature Reviews Drug Discovery, 2021Andres Cubillos-Ruiz +2 more
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Present and future of synthetic cell development
Nature Reviews Molecular Cell Biology, 2023Katarzyna P Adamala +2 more
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Semi-synthetic artemisinin: a model for the use of synthetic biology in pharmaceutical development
Nature Reviews Microbiology, 2014Christopher J Paddon, Jay D Keasling
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