Stars
A high-performance toolkit for atomistic simulations in JAX.
Equitrain: A Unified Framework for Training and Fine-tuning Machine Learning Interatomic Potentials
Awesome resources on normalizing flows.
A Python wrapper for extracting structured metadata from arXiv papers.
An R package to interpret mass spectra from different ionizations (ESI, APCI).
An R package to conduct statistics for certification of reference materials.
Materials Acceleration Platform Center at BAM
quacc is a flexible platform for computational materials science and quantum chemistry that is built for the big data era.
Code for automated fitting of machine learned interatomic potentials.
Official inference framework for 1-bit LLMs
🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics https://openreview.net/forum?id=SAT0KPA5UO
Collection of Tutorials on Machine Learning Interatomic Potentials
Statistical Rethinking Course for Jan-Mar 2023
pyiron - an integrated development environment (IDE) for computational materials science.
An evaluation framework for machine learning models simulating high-throughput materials discovery.
Autodiff is a numerical library for the Go programming language that supports automatic differentiation. It implements routines for linear algebra (vector/matrix operations), numerical optimization…
Bayesian analysis of ChIP-Seq data for the identification of transcription factor binding sites.
🔍 A Hex Editor for Reverse Engineers, Programmers and people who value their retinas when working at 3 AM.
SchNetPack - Deep Neural Networks for Atomistic Systems
Lab materials for MIT 3.320 and Harvard AP 275 courses on atomistic modeling
🌙 LunarVim is an IDE layer for Neovim. Completely free and community driven.