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Machine learning predictions for local electronic properties of disordered correlated electron systems

Machine learning predictions for local electronic properties of disordered correlated electron systems

Yi-Hsuan Liu
Sheng Zhang
Puhan Zhang
Ting-Kuo Lee
Gia-Wei Chern
ArXiv (abs)PDFHTML

Papers citing "Machine learning predictions for local electronic properties of disordered correlated electron systems"

6 / 6 papers shown
Title
Machine learning approach for vibronically renormalized electronic band structures
Machine learning approach for vibronically renormalized electronic band structures
Niraj Aryal
Sheng Zhang
Weiguo Yin
Gia-Wei Chern
155
0
0
03 Sep 2024
Kinetics of orbital ordering in cooperative Jahn-Teller models: Machine-learning enabled large-scale simulations
Kinetics of orbital ordering in cooperative Jahn-Teller models: Machine-learning enabled large-scale simulations
Supriyo Ghosh
Sheng Zhang
Chen Cheng
Gia-Wei Chern
41
1
0
23 May 2024
Coarsening of chiral domains in itinerant electron magnets: A machine learning force field approach
Coarsening of chiral domains in itinerant electron magnets: A machine learning force field approach
Yunhao Fan
Sheng Zhang
Gia-Wei Chern
51
1
0
18 Mar 2024
Machine learning for structure-property relationships: Scalability and limitations
Machine learning for structure-property relationships: Scalability and limitations
Zhongzheng Tian
Sheng Zhang
Gia-Wei Chern
31
2
0
11 Apr 2023
Machine learning for phase ordering dynamics of charge density waves
Machine learning for phase ordering dynamics of charge density waves
Chen Cheng
Sheng Zhang
Gia-Wei Chern
36
10
0
06 Mar 2023
Machine learning nonequilibrium electron forces for adiabatic spin dynamics
Machine learning nonequilibrium electron forces for adiabatic spin dynamics
Puhan Zhang
Gia-Wei Chern
44
16
0
22 Dec 2021