MIR@Harvard

nequip

NequIP is a code for building E(3)-equivariant interatomic potentials

allegro

Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials

flare

An open-source Python package for creating fast and accurate interatomic potentials.

pair_nequip

pair_allegro

LAMMPS pair style for Allegro deep learning interatomic potentials with parallelization support

flare_pp

A many-body extension of the FLARE code.

nequip-input-files

Input files for Batzner, S., Musaelian, A., Sun, L., Geiger, M., Mailoa, J. P., Kornbluth, M., ... & Kozinsky, B. (2021). E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials. arXiv preprint arXiv:2101.03164.

CiderPress

A high-performance software package for training and evaluating machine-learned XC functionals using the CIDER framework

EPA

Electron-phonon averaged approximation

CiderPress2022

Tools for training and evaluating CIDER functionals for use in Density Functional Theory calculations

BRAVE

Bloch Representation Analysis and Visualization Environment

CiderPressLite

"alpha" release of 2023 CIDER functionals, with interfaces to PySCF and GPAW

distmatrix

Simple C++ library for distributed matrices

nequip-example-extension

Example of how to implement an extension package to the `nequip` framework with custom loss terms, model components, etc.

surface-restructuring

Automated surface restructuring event characterization

MLmtCV-PLUMED-Plugin

pytorch_runstats

Running/online statistics for PyTorch

e3nn

A modular framework for neural networks with Euclidean symmetry

md

NDSimulator

An open-source python code for simple N-dimensional molecular dynamics and enhanced samplings

orchard

Fireworks-based workflow management for using and benchmarking ML/CIDER XC functionals.

surfator

"Atomic democracy" for site analysis of surfaces and bulks with known lattice structure(s).

FLARE-Tutorials

MLmtCV

real_harmonics

labutil

Lab materials for MIT 3.320 and Harvard AP 275 courses on atomistic modeling

nequip_mrs_tutorial

PyfileUtils