The Importance of Understanding Deep Learning.

IF 3.8 2区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES
Climate Dynamics Pub Date : 2024-01-01 Epub Date: 2022-08-07 DOI:10.1007/s10670-022-00605-y
Tim Räz, Claus Beisbart
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引用次数: 0

Abstract

Some machine learning models, in particular deep neural networks (DNNs), are not very well understood; nevertheless, they are frequently used in science. Does this lack of understanding pose a problem for using DNNs to understand empirical phenomena? Emily Sullivan has recently argued that understanding with DNNs is not limited by our lack of understanding of DNNs themselves. In the present paper, we will argue, contra Sullivan, that our current lack of understanding of DNNs does limit our ability to understand with DNNs. Sullivan's claim hinges on which notion of understanding is at play. If we employ a weak notion of understanding, then her claim is tenable, but rather weak. If, however, we employ a strong notion of understanding, particularly explanatory understanding, then her claim is not tenable.

了解深度学习的重要性。
有些机器学习模型,尤其是深度神经网络(DNN),并不十分为人所知;然而,它们却经常被用于科学领域。这种不理解是否会对使用 DNNs 理解经验现象造成问题?艾米丽-沙利文(Emily Sullivan)最近提出,使用 DNNs 理解并不会因为我们对 DNNs 本身缺乏了解而受到限制。在本文中,我们将反驳沙利文的观点,认为我们目前对 DNNs 的理解不足确实限制了我们利用 DNNs 理解的能力。沙利文的观点取决于哪种理解概念在起作用。如果我们使用的是一种弱理解概念,那么她的观点是站得住脚的,但相当薄弱。然而,如果我们使用的是强理解概念,尤其是解释性理解,那么她的说法就站不住脚了。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Climate Dynamics
Climate Dynamics 地学-气象与大气科学
CiteScore
8.80
自引率
15.20%
发文量
483
审稿时长
2-4 weeks
期刊介绍: The international journal Climate Dynamics provides for the publication of high-quality research on all aspects of the dynamics of the global climate system. Coverage includes original paleoclimatic, diagnostic, analytical and numerical modeling research on the structure and behavior of the atmosphere, oceans, cryosphere, biomass and land surface as interacting components of the dynamics of global climate. Contributions are focused on selected aspects of climate dynamics on particular scales of space or time. The journal also publishes reviews and papers emphasizing an integrated view of the physical and biogeochemical processes governing climate and climate change.
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