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- W4387007240 abstract "Air quality is a crucial environmental issue worldwide. The missing values in air quality datasets often impede further forecasting. To address this challenge, a transformer based model with spatio-temporal masked attention is proposed for simultaneous imputations of air quality values from multiple stations. Extensive experiments are conducted on a real dataset from Beijing city, demonstrating the effectiveness and superiority of the proposed model." @default.
- W4387007240 created "2023-09-26" @default.
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- W4387007240 date "2023-07-28" @default.
- W4387007240 modified "2023-09-26" @default.
- W4387007240 title "Efficient Air Quality Imputation with Transformer" @default.
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- W4387007240 doi "https://doi.org/10.1145/3603165.3607424" @default.
- W4387007240 hasPublicationYear "2023" @default.
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