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involves development of deep learning based synthetic data generators that obtain both good utility and protection of privacy, through tailored model approximation, as well as new measures of privacy and
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involves development of deep learning based synthetic data generators that obtain both good utility and protection of privacy, through tailored model approximation, as well as new measures of privacy and
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populations and biobanks for risk prediction, genetic discovery, and genomic medicine. Federated and transfer learning for distributed and privacy-preserving data integration. AI and Deep learning approaches
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