Update: 2024.05.23

📈 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.

• NequIP (🥇24 · ⭐ 540 · 📈) - NequIP is a code for building E(3)-equivariant interatomic potentials. MIT
• Open Catalyst datasets (🥇20 · ⭐ 660 · 📈) - The datasets of the Open Catalyst project, OC20, OC22. CC-BY-4.0
• ocp (🥈19 · ⭐ 660 · 📈) - ocp is the Open Catalyst Projects library of state-of-the-art machine learning algorithms for catalysis. Unlicensed
• Pre-trained OCP models (🥈19 · ⭐ 660 · 📈) - Pre-trained models released as part of the Open Catalyst Project. Unlicensed pre-trained
• Chemiscope (🥉17 · ⭐ 110 · 📈) - An interactive structure/property explorer for materials and molecules. BSD-3 JavaScript

📉 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.

• DeepChem (🥇36 · ⭐ 5.2K · 📉) - Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology. MIT
• SchNetPack (🥇26 · ⭐ 730 · 📉) - SchNetPack - Deep Neural Networks for Atomistic Systems. MIT
• TorchMD-NET (🥇21 · ⭐ 280 · 📉) - Neural network potentials. MIT MD rep-learn transformer pre-trained
• NVIDIA Deep Learning Examples for Tensor Cores (🥈20 · ⭐ 13K · 📉) - State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and.. Custom educational drug-discovery
• mp-pyrho (🥉17 · ⭐ 34 · 📉) - Tools for re-griding volumetric quantum chemistry data for machine-learning purposes. Custom ML-DFT

➕ Added Projects

Projects that were recently added to this best-of list.

• calorine (🥉8 · ⭐ 10 · 💀) - A Python package for constructing and sampling neuroevolution potential models. https://doi.org/10.21105/joss.06264. Custom
• PyNEP (🥉2 · ➕) - A python interface of the machine learning potential NEP used in GPUMD. MIT
• SOMD (🥉1 · ➕) - AGPL-3.0 ML-IAP active-learning
• apax (🥈18 · ⭐ 11 · ➕) - A flexible and performant framework for training machine learning potentials. MIT