Generative deep learning for data generation in natural hazard analysis: motivations, advances, challenges, and opportunities
Zhengjing Ma,
Gang Mei,
Nengxiong Xu
Abstract:Data mining and analysis are critical for preventing or mitigating natural hazards. However, data availability in natural hazard analysis is experiencing unprecedented challenges due to economic, technical, and environmental constraints. Recently, generative deep learning has become an increasingly attractive solution to these challenges, which can augment, impute, or synthesize data based on these learned complex, high-dimensional probability distributions of data. Over the last several years, much research h… Show more
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