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Sep, 2022
时空数据不确定性量化的共形方法综述
Conformal Methods for Quantifying Uncertainty in Spatiotemporal Data: A Survey
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Sophia Sun
TL;DR
本文调查了最近的深度学习方面的不确定性量化的研究，特别关注了具有数学特性和广泛适用性的无分布符合预测方法，介绍了相关技术和在时空数据背景下提高校准和效率的方法，并讨论了不确定性量化在安全决策方面的作用。
Abstract
machine learning
methods are increasingly widely used in
high-risk settings
such as healthcare, transportation, and finance. In these settings, it is important that a model produces calibrated uncertainty to refl
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