Few shot learning for Korean winter temperature forecasts

Few shot learning for Korean winter temperature forecasts

Abstract To address the challenge of limited training samples, this study employs the model-agnostic meta-learning (MAML) algorithm along with domain-knowledge-based data augmentation to predict winter temperatures on the Korean Peninsula. While data augmentation has been achieved by using global cl...

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Bibliographic Details
Main Authors:	Seol-Hee Oh, Yoo-Geun Ham
Format:	Article
Language:	English
Published:	Nature Portfolio 2024-11-01
Series:	npj Climate and Atmospheric Science
Online Access:	https://doi.org/10.1038/s41612-024-00813-z
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