most citedTowards Biologically Plausible and Private Gene Expression Data Generation

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

cs.CR2024★ 2 cited

Towards Biologically Plausible and Private Gene Expression Data Generation

Dingfan Chen, Marie Oestreich, Tejumade Afonja +3

Generative models trained with Differential Privacy (DP) are becoming increasingly prominent in the creation of synthetic data for downstream applications. Existing literature, how…