In many public healthcare systems, particularly in resource-constrained environments, time-series forecasting models offer a practical, interpretable, and evidence-based alternative (Stacey et al., ...
STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...
Abstract: We propose SAM-Road, an adaptation of the Segment Anything Model (SAM) [27] for extracting large-scale, vectorized road network graphs from satellite imagery. To predict graph geometry, we ...
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