40 citations · 86 across the 8 of their papers we have counts for
8 papers
Learning phase transitions by siamese neural network
Jianmin Shen, Shiyang Chen, Feiyi Liu +2
The wide application of machine learning (ML) techniques in statistics physics has presented new avenues for research in this field. In this paper, we introduce a semi-supervised l…
Applications of Domain Adversarial Neural Network in phase transition of 3D Potts model
Xiangna Chen, Feiyi Liu, Weibing Deng +5
Machine learning techniques exhibit significant performance in discriminating different phases of matter and provide a new avenue for studying phase transitions. We investigate the…
Supervised and unsupervised learning of (1+1)-dimensional even-offspring branching annihilating random walks
Yanyang Wang, Wei Li, Feiyi Liu +1
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 no…
Jet tagging algorithm of graph network with HaarPooling message passing
Fei Ma, Feiyi Liu, Wei Li
Recently methods of graph neural networks (GNNs) have been applied to solving the problems in high energy physics (HEP) and have shown its great potential for quark-gluon tagging w…
Study of phase transition of Potts model with Domain Adversarial Neural Network
Xiangna Chen, Feiyi Liu, Shiyang Chen +5
A transfer learning method, Domain Adversarial Neural Network (DANN), is introduced to study the phase transition of two-dimensional q-state Potts model. With the DANN, we only nee…
Transfer learning of phase transitions in percolation and directed percolation
Jianmin Shen, Feiyi Liu, Shiyang Chen +6
The latest advances of statistical physics have shown remarkable performance of machine learning in identifying phase transitions. In this paper, we apply domain adversarial neural…
Machine learning of pair-contact process with diffusion
Jianmin Shen, Wei Li, Shengfeng Deng +3
The pair-contact process with diffusion (PCPD), a generalized model of the ordinary pair-contact process (PCP) without diffusion, exhibits a continuous absorbing phase transition.…
Supervised and unsupervised learning of directed percolation
Jianmin Shen, Wei Li, Shengfeng Deng +1
Machine learning (ML) has been well applied to studying equilibrium phase transition models, by accurately predicating critical thresholds and some critical exponents. Difficulty w…