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📈 Trending Up

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

📉 Trending Down

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