TrajGANR: Trajectory-Centric Urban Multimodal Learning via Geospatially Aligned Neural Representations

Many urban prediction tasks depend not only on the static attributes of a location, such as the visual appearance of its built environment, but also on its dynamic function: how people navigate and use it over time. Predicting congestion, travel demand, or road safety risks, for instance, requires m