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DeePKS-kit

swMATH ID: 36441
Software Authors: Yixiao Chen, Linfeng Zhang, Han Wang, Weinan E
Description: DeePKS-kit: a package for developing machine learning-based chemically accurate energy and density functional models. We introduce DeePKS-kit, an open-source software package for developing machine learning based energy and density functional models. DeePKS-kit is interfaced with PyTorch, an open-source machine learning library, and PySCF, an ab initio computational chemistry program that provides simple and customized tools for developing quantum chemistry codes. It supports the DeePHF and DeePKS methods. In addition to explaining the details in the methodology and the software, we also provide an example of developing a chemically accurate model for water clusters.
Homepage: https://arxiv.org/abs/2012.14615
Source Code:  https://github.com/deepmodeling/deepks-kit
Keywords: Chemical Physics; arXiv_physics.chem-ph; Physics; arXiv_physics.comp-ph; machine learning; density functional theory; DFT
Related Software: GELUs; DP-GEN; Adam; PySCF; PyTorch
Cited in: 0 Publications

Standard Articles

1 Publication describing the Software Year
DeePKS-kit: a package for developing machine learning-based chemically accurate energy and density functional models
Yixiao Chen, Linfeng Zhang, Han Wang, Weinan E
2020