Projects that have a higher project-quality score compared to the last update. There might be a variety of reasons, such as increased downloads or code activity.
- Crystal Toolkit (🥇25 · ⭐ 160 · 📈) - Crystal Toolkit is a framework for building web apps for materials science and is currently powering the new Materials..
MIT
- dpdata (🥇24 · ⭐ 200 · 📈) - A Python package for manipulating atomistic data of software in computational science.
LGPL-3.0
- TorchMD-NET (🥇23 · ⭐ 360 · 📈) - Training neural network potentials.
MIT
MD
rep-learn
transformer
pretrained
- SALTED (🥇14 · ⭐ 31 · 📈) - Symmetry-Adapted Learning of Three-dimensional Electron Densities (and their electrostatic response).
GPL-3.0
- jarvis-tools-notebooks (🥇12 · ⭐ 74 · 📈) - A Google-Colab Notebook Collection for Materials Design: https://jarvis.nist.gov/.
NIST
Projects that have a lower project-quality score compared to the last update. There might be a variety of reasons such as decreased downloads or code activity.
- DeePMD-kit (🥇28 · ⭐ 1.6K · 📉) - A deep learning package for many-body potential energy representation and molecular dynamics.
LGPL-3.0
C++
- e3nn (🥇27 · ⭐ 1K · 📉) - A modular framework for neural networks with Euclidean symmetry.
MIT
- paper-qa (🥇25 · ⭐ 6.8K · 📉) - High accuracy RAG for answering questions from scientific documents with citations.
Apache-2
ai-agent
- JAX-MD (🥇24 · ⭐ 1.2K · 📉) - Differentiable, Hardware Accelerated, Molecular Dynamics.
Apache-2
- FLARE (🥇19 · ⭐ 310 · 📉) - An open-source Python package for creating fast and accurate interatomic potentials.
MIT
C++
ML-IAP