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Official implementation of ChargeE3Net, introduced in Higher-Order Equivariant Neural Networks for Charge Density Prediction in Materials.
SALTED: Symmetry-Adapted Learning of Three-dimensional Electron Densities This repository contains an implementation of symmetry-adapted Gaussian Process Regression suitable to perform equivariant learning and prediction of the electron density of molecular and condensed-phase systems, together…
DeePKS-kit is a program to generate accurate energy functionals for quantum chemistry systems, for both perturbative scheme (DeePHF) and self-consistent scheme (DeePKS).
The ACEhamiltonians package is a Julia package that provides tools for constructing, fitting, and predicting self-consistent Hamiltonian and overlap matrices in solid-state systems. It is based on the atomic cluster expansion (ACE) approach and the associated ACEsuit package. The ACEhamiltonians…
dftio is to assist machine learning communities to transcript DFT output into a format that is easy to read or used by machine learning models.
The main features of deepmodeling/dftio are: Density Functional Theory.
Open-source alternatives to deepmodeling/dftio include: acesuit/acehamiltonians.jl — The ACEhamiltonians package is a Julia package that provides tools for constructing, fitting, and predicting… aiforgreatgood/charge3net — Official implementation of ChargeE3Net, introduced in Higher-Order Equivariant Neural Networks for Charge Density… andreagrisafi/salted — SALTED: Symmetry-Adapted Learning of Three-dimensional Electron Densities This repository contains an implementation… deepmodeling/deepks-kit — DeePKS-kit is a program to generate accurate energy functionals for quantum chemistry systems, for both perturbative… divelab/airs — [license-image]:https://img.shields.io/badge/license-GPL3.0-green.svg [license-url]:https://github.com/divelab/AIRS/blo… google-research/google-research — This repository serves as a comprehensive research platform and toolkit for advancing machine learning, quantum…