A framework to facilitate the training and use of machine learning (ML) models in materials science and chemistry including interatomic potentials. Includes an online exchange for datasets used to train ML models and a portable format for deploying ML models to simulation platforms using the OpenKIM system.
FReSCo
Fast Reciprocal Space Correlator
OMatGenerate
Web tool for crystal structure prediction and de novo crystal generation using the OMatG model.
MAGreeTe
Materials Analysis through Green's Tensor — computational tool for electromagnetic analysis of materials.
dynamic-divisive-norm
PyTorch implementation of ORGaNICs — unconditionally stable recurrent neural circuits implementing divisive normalization (NeurIPS 2025).
SPECTRE
Algorithms for calculating the power spectral density of stochastic dynamical systems at fixed points.
KLIFF-Torch
PyTorch extension of the KLIFF interatomic model fitting package
libdescriptor
High performance descriptor library with Enzyme AD
basinerror
Accurate identification of basins of attraction
sweetsourcod
The sweet source-coding library (for entropy estimation)
pele
Python Energy Landscape Explorer
mcpele
Monte Carlo library for pele
nested sampling
Parallel Nested Sampling implementation
PyCG_DESCENT
Python wrapper for the Hager and Zhang CG_DESCENT algorithm
sens
Superposition Enhanced Nested Sampling