Xiang Li

发表

Generative adversarial networks (GAN) based efficient sampling of chemical composition space for inverse design of inorganic materials

Jianjun Hu, Yabo Dan, Shaobo Li, 2019, npj Computational Materials.

BASED C RYSTAL STRUCTURE PREDICTION USING GLOBAL OPTIMIZATION

Xiang Li, Shaobo Li, Jianjun Hu, 2020 .

Convolutional Neural Networks for Crystal Material Property Prediction Using Hybrid Orbital-Field Matrix and Magpie Descriptors

Jianjun Hu, Xiang Li, Yabo Dan, 2019, Crystals.

Contact map based crystal structure prediction using global optimization

Edirisuriya M. D. Siriwardane, Xiang Li, Shaobo Li, 2020, CrystEngComm.

Inverse design of composite metal oxide optical materials based on deep transfer learning and global optimization

Yabo Dan, Rongzhi Dong, Xiang Li, 2020, 2008.10618.

Critical Temperature Prediction of Superconductors Based on Atomic Vectors and Deep Learning

Yabo Dan, Rongzhi Dong, Shaobo Li, 2020, Symmetry.

Fermionic neural network with effective core potential

Xiang Li, Weiluo Ren, Ji Chen, 2021, Physical Review Research.

Computational Prediction of Critical Temperatures of Superconductors Based on Convolutional Gradient Boosting Decision Trees

Jianjun Hu, Xiang Li, Yabo Dan, 2020, IEEE Access.

Computational Screening of New Perovskite Materials Using Transfer Learning and Deep Learning

Li Xiang, Rongzhi Dong, Shaobo Li, 2019, Applied Sciences.

Generative adversarial networks (GAN) based efficient sampling of chemical composition space for inverse design of inorganic materials pdf

Xiang Li, Yabo Dan, Shaobo Li, 2019, npj Computational Materials.

Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo

Liwei Wang, Xiang Li, Di He, 2023, ArXiv.

Inverse design of composite metal oxide optical materials based on deep transfer learning and global optimization

Yabo Dan, Xiang Li, Jianjun Hu, 2020, Computational Materials Science.