Universal Scaling Laws of Absorbing Phase Transitions in Artificial Deep Neural Networks

We demonstrate that conventional artificial deep neural networks operating near the phase boundary of the signal propagation dynamics, also known as the edge of chaos, exhibit universal scaling laws of absorbing phase transitions in non-equilibrium statistical mechanics. Our numerical results indica...

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Hauptverfasser:	Tamai, Keiichi, Okubo, Tsuyoshi, Duy, Truong Vinh Truong, Natori, Naotake, Todo, Synge
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Physics - Disordered Systems and Neural Networks Physics - Statistical Mechanics Statistics - Machine Learning
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