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Found 2 papers, 2 papers with code
Assessing Differentially Private Variational Autoencoders under Membership Inference
We present an approach to quantify and compare the privacy-accuracy trade-off for differentially private Variational Autoencoders.
Assessing differentially private deep learning with Membership Inference
We empirically compare local and central differential privacy mechanisms under white- and black-box membership inference to evaluate their relative privacy-accuracy trade-offs.
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