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The intersection of VAE and RDP lies in their shared goal of enhancing data utility while preserving privacy. By integrating RDP mechanisms into the VAE training process, researchers can generate models that are not only capable of producing realistic synthetic data but do so in a privacy-preserving manner By integrating RDP mechanisms into the VAE training process, researchers can generate models that are not only capable of producing realistic synthetic data but do so in a privacy-preserving manner By integrating RDP mechanisms into the VAE training process, researchers can generate models that are not only capable of producing realistic synthetic data but do so in a privacy-preserving manner By integrating RDP mechanisms into the VAE training process, researchers can generate models that are not only capable of producing realistic synthetic data but do so in a privacy-preserving mannervae rdp. This combination ensures that as the autoencoder learns to reconstruct and generate data, it does so within the constraints of maintaining individual privacy.