40 citations · 70 across the 9 of their papers we have counts for
4 papers · 1 filter
Efficient Calculation of NMR Shielding Constants Using Composite Method Approximations and Locally Dense Basis Sets
Jiashu Liang, Zhe Wang, Jie Li +5
This paper presents a systematic study of applying composite method approximations with locally dense basis sets (LDBS) to efficiently calculate NMR shielding constants in small an…
NewtonNet: A Newtonian message passing network for deep learning of interatomic potentials and forces
Mojtaba Haghighatlari, Jie Li, Xingyi Guan +10
We report a new deep learning message passing network that takes inspiration from Newton's equations of motion to learn interatomic potentials and forces. With the advantage of dir…
Learning to Make Chemical Predictions: the Interplay of Feature Representation, Data, and Machine Learning Algorithms
Mojtaba Haghighatlari, Jie Li, Farnaz Heidar-Zadeh +3
Recently supervised machine learning has been ascending in providing new predictive approaches for chemical, biological and materials sciences applications. In this Perspective we…
A Multi-Resolution 3D-DenseNet for Chemical Shift Prediction in NMR Crystallography
Shuai Liu, Jie Li, Kochise C. Bennett +6
We have developed a deep learning algorithm for chemical shift prediction for atoms in molecular crystals that utilizes an atom-centered Gaussian density model for the 3D data repr…