AI RESEARCH
Prior Knowledge-enhanced Spatio-temporal Epidemic Forecasting
arXiv CS.LG
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ArXi:2602.22270v2 Announce Type: replace Spatio-temporal epidemic forecasting is critical for public health management, yet existing methods often struggle with insensitivity to weak epidemic signals, over-simplified spatial relations, and unstable parameter estimation. To address these challenges, we propose the Spatio-Temporal priOr-aware Epidemic Predictor (STOEP), a novel hybrid framework that integrates implicit spatio-temporal priors and explicit expert priors.