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A Brief Tour of Deep Learning from a Statistical Perspective
Annual Review of Statistics and Its Application ( IF 7.9 ) Pub Date : 2023-03-09 , DOI: 10.1146/annurev-statistics-032921-013738
Eric Nalisnick 1 , Padhraic Smyth 2 , Dustin Tran 3
Affiliation  

We expose the statistical foundations of deep learning with the goal of facilitating conversation between the deep learning and statistics communities. We highlight core themes at the intersection; summarize key neural models, such as feedforward neural networks, sequential neural networks, and neural latent variable models; and link these ideas to their roots in probability and statistics. We also highlight research directions in deep learning where there are opportunities for statistical contributions.

中文翻译:

从统计角度简要介绍深度学习

我们揭示深度学习的统计基础,目的是促进深度学习和统计社区之间的对话。我们突出交叉点的核心主题;总结关键的神经模型,例如前馈神经网络、顺序神经网络和神经潜变量模型;并将这些想法与其概率论和统计学的根源联系起来。我们还重点介绍深度学习的研究方向,其中有机会做出统计贡献。
更新日期:2023-03-09
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