Abhilash Singh
@abhilashsingh.bsky.social
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University of Leeds|[email protected]|Machine Learning|Artificial Intelligence|Hydrology|Remote Sensing|Codes: https://abhilashsingh.net/codes.html
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Worried about missing value?
A novel imputation framework based on Fourier neural operators (FNO) for soil moisture. The FNO model outperforms traditional approaches, and incorporating temporal lag reduces error by up to 15% in the diverse climates in India and Zambia.
doi.org/10.1029/2025...
A novel imputation framework based on Fourier neural operators (FNO) for soil moisture. The FNO model outperforms traditional approaches, and incorporating temporal lag reduces error by up to 15% in the diverse climates in India and Zambia.
doi.org/10.1029/2025...
Leveraging Neural Operator and Sliding Window Technique for Enhanced Subsurface Soil Moisture Imputation Under Diverse Precipitation Scenarios
Developed a novel Fourier Neural Operator (FNO) to enhance subsurface soil moisture imputation by employing a sliding window concept that seamlessly integrates rainfall, soil temperature, and norm...
doi.org
Abhilash Singh
@abhilashsingh.bsky.social
· Jul 23