NoisyFlow: differentially private optimal transport using neural networks for secure biomedical data sharing across multiple institutions.
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| Title: | NoisyFlow: differentially private optimal transport using neural networks for secure biomedical data sharing across multiple institutions. |
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| Authors: | Li Y; Department of Computer Science, Yale University, New Haven, CT 06511, United States., Khandekar N; Department of Computer Science, Yale University, New Haven, CT 06511, United States., Wang S; Department of Computer Science, Yale University, New Haven, CT 06511, United States., Khanna V; Department of Biostatistics, Yale School of Public Health, New Haven, CT 06511, United States., Sanker J; Department of Computer Science, Yale University, New Haven, CT 06511, United States., Gerstein MB; Department of Computer Science, Yale University, New Haven, CT 06511, United States.; Program in Computational Biology and Biomedical Informatics, Yale University, New Haven, CT 06511, United States.; Department of Statistics and Data Science, Yale University, New Haven, CT 06511, United States. |
| Source: | Bioinformatics (Oxford, England) [Bioinformatics] 2026 Jul 01; Vol. 42 (Supplement_1). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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