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Synthetic Human Mobility Data Generation: A Structured Review of Representations, Methods, and Practical Capabilities
Human mobility data has become an increasingly important component of urban analytics. Although the range of available mobility data sources has expanded substantially, access remains highly constrained by commercial restrictions, privacy concerns, and institutional barriers. Data protection procedures also often reduc...
DiffPTS: Rethinking Diffusion ELBO for Probabilistic Time Series Forecasting
Probabilistic time series forecasting requires modeling and predicting complex and time-varying distributions. Recently, Denoising Diffusion Probabilistic Model (DDPM)-based approaches have shown promise by equipping the dif- fusion process with pretrained mean and variance estimators to accommodate distributional shif...