activity
20192026
most citedDeep Density: circumventing the Kohn-Sham equations via symmetry preserving neural networks

13 citations · 13 across the 5 of their papers we have counts for

collaborators
Showing 2019Show all

2 papers · 1 filter

math.NA2019

Universal approximation of symmetric and anti-symmetric functions

Jiequn Han, Yingzhou Li, Lin Lin +3

We consider universal approximations of symmetric and anti-symmetric functions, which are important for applications in quantum physics, as well as other scientific and engineering…

physics.comp-ph2019★ 13 cited

Deep Density: circumventing the Kohn-Sham equations via symmetry preserving neural networks

Leonardo Zepeda-Núñez, Yixiao Chen, Jiefu Zhang +3

The recently developed Deep Potential [Phys. Rev. Lett. 120, 143001, 2018] is a powerful method to represent general inter-atomic potentials using deep neural networks. The success…