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MACE foundation models (MP, OMAT, Matpes)
Python package to construct free energy profiles from biased molecular simulation data using both log-likelihood maximization and self-consistent iteration approaches.
An Educational Hartree-Fock Code in Python: Transparent Implementation of Gaussian-Type Integrals, SCF Procedures, and Geometry Optimization
⚡ Triton implementation of Clifford algebra neural networks.
Sum-of-Gaussians Neural Network (SOG-Net) is a lightweight and versatile framework for integrating long-range interactions into machine learning force field.
sGDML - Reference implementation of the Symmetric Gradient Domain Machine Learning model
Reciprocal Space Attention (RSA) for Learning Long-Range Interactions
A flexible and performant framework for training machine learning potentials.
Code to create EC interface calculations with VASP and extract data
This is a simple script to plot energy profile diagrams using Python and matplotlib.
Tool to draw reaction energy diagrams, reaction energies and reaction energetics using Python and matplotlib
Efficient misspecification uncertainties for linear regression
Portable file server with accelerated resumable uploads, dedup, WebDAV, FTP, TFTP, zeroconf, media indexer, thumbnails++ all in one file, no deps
A Python package for estimating diffusion properties from molecular dynamics simulations.
Annotated implementations of equivariant (graph) neural networks in Jax: EGNN, SEGNN, NequIP.
AI-powered ab initio biomolecular dynamics simulation
Library for efficient training and application of Machine Learning Interatomic Potentials (MLIP)
A scientific machine learning (SciML) wrapper for the FEniCS Finite Element library in the Julia programming language
Graph neural network potential with charge transfer
Interactive browser visualizations for materials science: periodic tables, 3d crystal structures, MD trajectories, heatmaps, scatter plots, histograms.
Packmol - Initial configurations for molecular dynamics simulations