Synthetic location trajectory generation using categorical diffusion models

arXiv:2402.12242v1 Announce Type: new
Abstract: Diffusion probabilistic models (DPMs) have rapidly evolved to be one of the predominant generative models for the simulation of synthetic data, for instance, for computer vision, audio, natural language processing, or biomolecule generation. Here, we propose using DPMs for the generation of synthetic individual location trajectories (ILTs) which are sequences of variables representing physical locations visited by individuals. ILTs are of major importance in mobility research to understand the mobility behavior of populations and to …

abstract arxiv audio categorical computer computer vision cs.lg data diffusion diffusion models generative generative models instance language language processing location natural natural language natural language processing processing simulation synthetic synthetic data the simulation trajectory type vision