Symmetrical Graph Neural Network for Quantum Chemistry, with Dual R/K Space

no code implementations • 16 Dec 2019 • Shuqian Ye, Jiechun Liang, Rulin Liu, Xi Zhu

Most of current neural network models in quantum chemistry (QC) exclude the molecular symmetry, separate the well-correlated real space (R space), and momenta space (K space) into two individuals, which lack the essential physics in molecular chemistry.

Chemical Physics

Pixel Chem: A Representation for Predicting Material Properties with Neural Network

no code implementations • 27 Sep 2018 • Shuqian Ye, Yanheng Xu, Jiechun Liang, Hao Xu, Shuhong Cai, Shixin Liu, Xi Zhu

In this work we developed a new representation of the chemical information for the machine learning models, with benefits from both the real space (R-space) and energy space (K-space).

BIG-bench Machine Learning