A masked conditional diffusion model with historical user embeddings simultaneously performs trajectory generation, recovery, and prediction, beating task-specific baselines on two datasets.
Enhancing human mobility research with open and standardized datasets,
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One Fits All: General Mobility Trajectory Modeling via Masked Conditional Diffusion
A masked conditional diffusion model with historical user embeddings simultaneously performs trajectory generation, recovery, and prediction, beating task-specific baselines on two datasets.