arxiv
PublishedJuly 15, 2026 at 4:00 AM
OmniPMNet: Bridging discrete and gridded PM10 forecasts via omni-query neural processes
Publisher summary· verbatim
arXiv:2607.11896v1 Announce Type: cross Abstract: Forecasting particulate matter (PM10) requires both station-scale accuracy and continuous spatial fields, especially during severe dust storms. Chemical transport models (CTMs) provide gridded forecasts but retain local biases, whereas graph neural n
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Originally published on arxiv ↗