17 citations · 45 across the 15 of their papers we have counts for
4 papers · 1 filter
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.…
Machine learning Hadron Spectral Functions in Lattice QCD
Shi-Yang Chen, Heng-Tong Ding, Fei-Yi Liu +2
Hadron spectral functions carry all the information of hadrons and are encoded in the Euclidean two-point correlation functions. The extraction of hadron spectral functions from th…
Machine learning spectral functions in lattice QCD
S. -Y. Chen, H. -T. Ding, F. -Y. Liu +2
We study the inverse problem of reconstructing spectral functions from Euclidean correlation functions via machine learning. We propose a novel neural network, SVAE, which is based…