294 citations · 338 across the 5 of their papers we have counts for
5 papers
Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo
Ruichen Li, Haotian Ye, Du Jiang +8
Neural network-based variational Monte Carlo (NN-VMC) has emerged as a promising cutting-edge technique of ab initio quantum chemistry. However, the high computational cost of exis…
Fermionic Neural Network with Effective Core Potential
Xiang Li, Cunwei Fan, Weiluo Ren +1
Deep learning techniques have opened a new venue for electronic structure theory in recent years. In contrast to traditional methods, deep neural networks provide much more express…
Inverse Design of Composite Metal Oxide Optical Materials based on Deep Transfer Learning
Rongzhi Dong, Yabo Dan, Xiang Li +1
Optical materials with special optical properties are widely used in a broad span of technologies, from computer displays to solar energy utilization leading to large dataset accum…
Contact Map based Crystal Structure Prediction using Global Optimization
Jianjun Hu, Wenhui Yang, Rongzhi Dong +3
Crystal structure prediction is now playing an increasingly important role in discovery of new materials. Global optimization methods such as genetic algorithms (GA) and particle s…
Generative adversarial networks (GAN) based efficient sampling of chemical space for inverse design of inorganic materials
Yabo Dan, Yong Zhao, Xiang Li +3
A major challenge in materials design is how to efficiently search the vast chemical design space to find the materials with desired properties. One effective strategy is to develo…