A new framework evaluates utility of synthetic mobility trajectories while a membership inference attack reveals privacy vulnerabilities in generative models thought to be safe.
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Transformer-GCN model reconstructs high-resolution GPS trajectories from low-resolution inputs, reporting 0.198 km average Fréchet distance on Beijing data and outperforming map-matching and LSTM baselines.
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A Dual Perspective on Synthetic Trajectory Generators: Utility Framework and Privacy Vulnerabilities
A new framework evaluates utility of synthetic mobility trajectories while a membership inference attack reveals privacy vulnerabilities in generative models thought to be safe.
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Restoring Super-High Resolution GPS Mobility Data
Transformer-GCN model reconstructs high-resolution GPS trajectories from low-resolution inputs, reporting 0.198 km average Fréchet distance on Beijing data and outperforming map-matching and LSTM baselines.