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Physical Review Research

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Frontiers of Physics (1)J Mol Model (1)

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Universal scaling laws of absorbing phase transitions in artificial deep neural networks

Keiichi Tamai ^1,*, Tsuyoshi Okubo ¹, Truong Vinh Truong Duy ², Naotake Natori², and Synge Todo ^3,1,4

¹Institute for Physics of Intelligence, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
²AI Laboratory, Aisin Corporation, 1-18-13 Sotokanda, Chiyoda-ku, Tokyo 101-0021, Japan
³Department of Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
⁴Institute for Solid State Physics, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8581, Japan

^*Contact author: tamai@phys.s.u-tokyo.ac.jp

Deep learning theory through the lens of statistical physics: A topical review

Wei Huang and Youjin Deng

Frontiers of Physics 22 011302 (2027)

Study on the mechanical properties and critical temperature of FeNiCrMn alloy using MD-ML-MA framework

Jing Liu, Jinyuan Mao, Bin Wang, Qiankun Wang, Nan Zhang, and Shiyi Pan

J Mol Model 31 340 (2025)

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