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chemiscope
An interactive structure/property explorer for materials and moleculeslibrascal
A scalable and versatile library to generate representations for atomic-scale learningsphericart
Multi-language library for the calculation of spherical harmonics in Cartesian coordinatesmetatensor
Self-describing sparse tensor data format for atomistic machine learning and beyondsketchmap
Suite of programs to perform non-linear dimensionality reduction -- sketch-map in particularglosim
A Python package to compute similarities between molecules and structuresi-pi-dev_archive
Development version of i-PISA-GPR
kernel-tutorials
A set of utilities and pedagogic notebooks for the use of linear and kernel methods in atomistic modelingatomistic-cookbook
The COSMO cookbook contains recipes for atomic-scale modelling for materials and moleculesmetatrain
Training and evaluating machine learning models for atomistic systems.pimd-tutorial
Inputs and hand-outs for a PIMD tutorial based on i-PInice
glosim2
A rehaul of the glosim code, adding new features and removing many unused ones.sparse_accumulation
sphericart_torch
Spherical harmonics in Pytorchpamm
Tools for the Probabilistic Analysis of Molecular Motifs methodtoolbox
Assorted libraries and utilities for atomistic simulation analysismops
Mathematical operations with GPU accelerationequisolve
A ML toolkit package utilizing the metatensor data format to build models for the prediction of equivariant properties and gradients.ncenter-reps
A repository showcasing the construction of N-center features and Hamiltonian learningcosmo-tools
Scripts, jupyter nbs, and general helpful stuff from COSMO by COSMOisv
An Interactive Sketch-Map Visualizertorch_spex
Spherical expansions in PyTorchwigner_kernels
marvel-college
Teaching materials for a high-school programming camp.github
COSMO Github Pagelab-cosmo.github.io
Webpages for the code repositories of the Laboratory of Computational Science and Modelling @ EPFLequistore-examples
ch4-manifold-training
sampling-tutorial
Exercise files and handouts for a sampling tutorial, from thermostatting to non-linear dimentionality reductionLove Open Source and this site? Check out how you can help us