Adapting Transformer Encoder Architecture for Continuous Weather Datasets with Applications in Agriculture, Epidemiology and Climate Science
This work introduces WeatherFormer, a transformer encoder-based model designed to robustly represent weather data from minimal observations. It addresses the challenge of modeling complex weather dynamics from small datasets, which is a bottleneck for many prediction tasks in agriculture, epidemiolo...
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Format: | Thesis |
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Massachusetts Institute of Technology
2024
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Online Access: | https://hdl.handle.net/1721.1/156822 |