diffGHOST is a conditional diffusion model that segments learned latent space to identify and mitigate memorization of critical trajectory samples, aiming to deliver privacy guarantees alongside data utility.
Sok: Can trajectory generation combine privacy and utility?
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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Generative models for trajectory data do not inherently preserve privacy, as membership inference attacks can identify training data points in representative models.
citing papers explorer
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diffGHOST: Diffusion based Generative Hedged Oblivious Synthetic Trajectories
diffGHOST is a conditional diffusion model that segments learned latent space to identify and mitigate memorization of critical trajectory samples, aiming to deliver privacy guarantees alongside data utility.
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Privacy Evaluation of Generative Models for Trajectory Generation
Generative models for trajectory data do not inherently preserve privacy, as membership inference attacks can identify training data points in representative models.