40 citations · 68 across the 13 of their papers we have counts for
4 papers · 1 filter
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…
Identifying percolation phase transitions with unsupervised learning based on largest clusters
Dian Xu, Shanshan Wang, Weibing Deng +3
The application of machine learning in the study of phase transitions has achieved remarkable success in both equilibrium and non-equilibrium systems. It is widely recognized that…
Machine learning of (1+1)-dimensional directed percolation based on raw and shuffled configurations
Shen Jianmin, Wang Shanshan, Li Wei +6
Machine learning (ML) can process large sets of data generated from complex systems, which is ideal for classification tasks as often appeared in critical phenomena. Meanwhile ML t…
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…