Supervised and unsupervised learning of -dimensional even-offspring branching annihilating random walks

Supervised and unsupervised learning of -dimensional even-offspring branching annihilating random walks

Machine learning (ML) of phase transitions (PTs) has gradually become an effective approach that enables us to explore the nature of various PTs more promptly in equilibrium and nonequilibrium systems. Unlike equilibrium systems, non-equilibrium systems display more complicated and diverse features...

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Bibliographic Details
Main Authors: Yanyang Wang, Wei Li, Feiyi Liu, Jianmin Shen
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:Machine Learning: Science and Technology
Subjects:
machine learning
non-equilibrium phase transitions
branching annihilating random walks
convolutional neural networks
autoencoder
Online Access:https://doi.org/10.1088/2632-2153/ad27e2

Internet

https://doi.org/10.1088/2632-2153/ad27e2

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