40 citations · 86 across the 8 of their papers we have counts for
4 papers · 1 filter
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…