A grid-free deep learning model predicts high-resolution surface PM2.5 concentrations in near real time by combining sparse EPA station data with topographic, meteorological, and land-use inputs.
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A grid-free attention-based deep learning model interpolates surface-level PM2.5 concentrations across the US using sparse sensor data and auxiliary geospatial features.
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Mechanistic Anomaly Detection via Functional Attribution
A grid-free attention-based deep learning model interpolates surface-level PM2.5 concentrations across the US using sparse sensor data and auxiliary geospatial features.