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深度学习统计力学

IF 14.3 1区 物理与天体物理 Q1 PHYSICS, CONDENSED MATTER
Annual Review of Condensed Matter Physics Pub Date : 2020-03-16 DOI:10.1146/annurev-conmatphys-031119-050745
Yasaman Bahri, Jonathan Kadmon, Jeffrey Pennington, S. Schoenholz, Jascha Narain Sohl-Dickstein, S. Ganguli
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引用次数: 171

摘要

最近，深度神经网络在机器学习领域取得了惊人的成功，这引发了人们对其成功背后的理论原理的深刻质疑。例如，这样的深度网络……
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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Statistical Mechanics of Deep Learning
The recent striking success of deep neural networks in machine learning raises profound questions about the theoretical principles underlying their success. For example, what can such deep networks...
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来源期刊
Annual Review of Condensed Matter Physics
Annual Review of Condensed Matter Physics PHYSICS, CONDENSED MATTER-
CiteScore
47.40
自引率
0.90%
发文量
27
期刊介绍： Since its inception in 2010, the Annual Review of Condensed Matter Physics has been chronicling significant advancements in the field and its related subjects. By highlighting recent developments and offering critical evaluations, the journal actively contributes to the ongoing discourse in condensed matter physics. The latest volume of the journal has transitioned from gated access to open access, facilitated by Annual Reviews' Subscribe to Open initiative. Under this program, all articles are now published under a CC BY license, ensuring broader accessibility and dissemination of knowledge.
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