Update: 2024.08.19-13.22

Removed category biomolecules in accordance with issue #125.

Update: 2024.08.15

📈 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.

• paper-qa (🥇27 · ⭐ 3.8K · 📈) - LLM Chain for answering questions from documents with citations. Apache-2 ai-agent
• DScribe (🥇23 · ⭐ 390 · 📈) - DScribe is a python package for creating machine learning descriptors for atomistic systems. Apache-2
• pymatviz (🥇21 · ⭐ 150 · 📈) - A toolkit for visualizations in materials informatics. MIT general-tool probabilistic
• e3nn-jax (🥈20 · ⭐ 170 · 📈) - jax library for E3 Equivariant Neural Networks. Apache-2

📉 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.

• dpdata (🥇23 · ⭐ 200 · 📉) - Manipulating multiple atomic simulation data formats, including DeePMD-kit, VASP, LAMMPS, ABACUS, etc. LGPL-3.0
• Best-of Machine Learning with Python (🥇21 · ⭐ 16K · 📉) - A ranked list of awesome machine learning Python libraries. Updated weekly. CC-BY-4.0 general-ml Python
• Open Databases Integration for Materials Design (OPTIMADE) (🥈17 · ⭐ 76 · 📉) - Specification of a common REST API for access to materials databases. CC-BY-4.0
• openmm-torch (🥈16 · ⭐ 180 · 📉) - OpenMM plugin to define forces with neural networks. Custom ML-IAP C++
• MatBench Discovery (🥈16 · ⭐ 82 · 📉) - An evaluation framework for machine learning models simulating high-throughput materials discovery. MIT datasets benchmarking model-repository

➕ Added Projects

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

• QH9 (🥈12 · ⭐ 470 · ➕) - A Quantum Hamiltonian Prediction Benchmark. CC-BY-NC-SA 4.0 ML-DFT
• DPA-2 (🥇26 · ⭐ 1.4K · ➕) - Towards a universal large atomic model for molecular and material simulation https://doi.org/10.48550/arXiv.2312.15492. LGPL-3.0 ML-IAP pretrained workflows datasets
• Graphormer (🥈16 · ⭐ 2K · ➕) - Graphormer is a general-purpose deep learning backbone for molecular modeling. MIT transformer pretrained
• OpenML (🥈16 · ⭐ 660 · 💤) - Open Machine Learning. BSD-3 datasets
• PMTransformer (🥇16 · ⭐ 82 · ➕) - Universal Transfer Learning in Porous Materials, including MOFs. MIT transfer-learning pretrained transformer
• SevenNet (🥉14 · ⭐ 86 · ➕) - SevenNet (Scalable EquiVariance Enabled Neural Network) is a graph neural network interatomic potential package that.. GPL-3.0 ML-IAP MD pretrained
• HydraGNN (🥈14 · ⭐ 56 · ➕) - Distributed PyTorch implementation of multi-headed graph convolutional neural networks. BSD-3
• ChatMOF (🥈13 · ⭐ 53 · ➕) - Predict and Inverse design for metal-organic framework with large-language models (llms). MIT generative
• MACE-MP (🥉12 · ⭐ 33 · ➕) - Pretrained foundation models for materials chemistry. MIT ML-IAP pretrained rep-learn MD
• Neural-Network-Models-for-Chemistry (🥈11 · ⭐ 59 · ➕) - A collection of Nerual Network Models for chemistry. Unlicensed rep-learn
• load-atoms (🥈11 · ⭐ 37 · ➕) - download and manipulate atomistic datasets. MIT data-structures
• AI4Chemistry course (🥈10 · ⭐ 130 · ➕) - EPFL AI for chemistry course, Spring 2023. https://schwallergroup.github.io/ai4chem_course. MIT chemistry
• HamGNN (🥈9 · ⭐ 49 · ➕) - An E(3) equivariant Graph Neural Network for predicting electronic Hamiltonian matrix. GPL-3.0 rep-learn magnetism C-lang
• AI for Science paper collection (🥉9 · ⭐ 43 · 🐣) - List the AI for Science papers accepted by top conferences. Apache-2
• Q-stack (🥈9 · ⭐ 14 · ➕) - Stack of codes for dedicated pre- and post-processing tasks for Quantum Machine Learning (QML). MIT excited-states general-tool
• MADICES Awesome Interoperability (🥉9 · ⭐ 1 · ➕) - Linked data interoperability resources of the Machine-actionable data interoperability for the chemical sciences.. MIT datasets
• Awesome-Graph-Generation (🥉8 · ⭐ 260 · ➕) - A curated list of up-to-date graph generation papers and resources. Unlicensed rep-learn
• Awesome Neural SBI (🥉8 · ⭐ 80 · ➕) - Community-sourced list of papers and resources on neural simulation-based inference. MIT active-learning
• SiMGen (🥉8 · ⭐ 11 · ➕) - Zero Shot Molecular Generation via Similarity Kernels. MIT viz
• Awesome-Crystal-GNNs (🥉7 · ⭐ 54 · ➕) - This repository contains a collection of resources and papers on GNN Models on Crystal Solid State Materials. MIT
• AIS Square (🥉7 · ⭐ 10 · 💤) - A collaborative and open-source platform for sharing AI for Science datasets, models, and workflows. Home of the.. LGPL-3.0 community-resource model-repository
• rho_learn (🥉7 · ⭐ 3 · ➕) - A proof-of-concept framework for torch-based learning of the electron density and related scalar fields. MIT
• ChargE3Net (🥉6 · ⭐ 28 · ➕) - Higher-order equivariant neural networks for charge density prediction in materials. <a href="http://bit.ly/34MB...

Update: 2024.07.04

📈 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.

• DeePMD-kit (🥇28 · ⭐ 1.4K · 📈) - A deep learning package for many-body potential energy representation and molecular dynamics. LGPL-3.0 C++
• SchNetPack (🥇26 · ⭐ 750 · 📈) - SchNetPack - Deep Neural Networks for Atomistic Systems. MIT
• QUIP (🥈25 · ⭐ 340 · 📈) - libAtoms/QUIP molecular dynamics framework: https://libatoms.github.io. GPL-2.0 MD ML-IAP rep-eng Fortran
• Ultra-Fast Force Fields (UF3) (🥈15 · ⭐ 55 · 📈) - UF3: a python library for generating ultra-fast interatomic potentials. Apache-2
• SchNetPack G-SchNet (🥈14 · ⭐ 42 · 📈) - G-SchNet extension for SchNetPack. MIT

📉 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.

• GPUMD (🥇21 · ⭐ 410 · 📉) - GPUMD is a highly efficient general-purpose molecular dynamic (MD) package and enables machine-learned potentials.. GPL-3.0 MD C++ electrostatics
• DP-GEN (🥇21 · ⭐ 280 · 📉) - The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field. LGPL-3.0 workflows
• DIG: Dive into Graphs (🥈20 · ⭐ 1.8K · 📉) - A library for graph deep learning research. GPL-3.0
• gpax (🥇17 · ⭐ 190 · 📉) - Gaussian Processes for Experimental Sciences. MIT probabilistic active-learning
• SPICE (🥈11 · ⭐ 130 · 📉) - A collection of QM data for training potential functions. MIT ML-IAP MD

➕ Added Projects

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

• LLaMP (🥈11 · ⭐ 36 · ➕) - A web app and Python API for multi-modal RAG framework to ground LLMs on high-fidelity materials informatics. An.. BSD-3 materials-discovery cheminformatics generative MD language-models Python
• IPSuite (🥈14 · ⭐ 14 · ➕) - IPSuite is a Python toolkit for FAIR development and deployment of MLPs. EPL-2.0 workflows HTC Python active-learning community-resource MD
• ZnDraw (🥉16 · ⭐ 23 · ➕) - A powerful tool for visualizing, modifying, and analysing atomistic systems. EPL-2.0 MD generative JavaScript
• FAIR Chemistry datasets (🥇21 · ⭐ 700 · ➕) - Datasets OC20, OC22, etc. Formerly known as Open Catalyst Project. MIT catalysis
• fairchem (🥈19 · ⭐ 700 · ➕) - FAIR Chemistrys library of machine learning methods for chemistry. Formerly known as Open Catalyst Project (ocp). Unlicensed pre-trained rep-learn catalysis

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

Update: 2024.03.17

📈 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.

• cdk (🥇24 · ⭐ 460 · 📈) - The Chemistry Development Kit. LGPL-2.1 cheminformatics Java
• AI for Science Resources (🥈14 · ⭐ 360 · 📈) - List of resources for AI4Science research, including learning resources. GPL-3.0 license
• QH9: A Quantum Hamiltonian Prediction Benchmark (🥈14 · ⭐ 360 · 📈) - Artificial Intelligence Research for Science (AIRS). CC-BY-NC-SA 4.0 ML-DFT
• Artificial Intelligence for Science (AIRS) (🥉14 · ⭐ 360 · 📈) - Artificial Intelligence Research for Science (AIRS). GPL-3.0 license rep-learn generative ML-IAP MD ML-DFT ML-WFT biomolecules
• QHNet (🥈14 · ⭐ 360 · 📈) - Artificial Intelligence Research for Science (AIRS). GPL-3.0 rep-learn

📉 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.

• TorchMD-NET (🥇22 · ⭐ 270 · 📉) - Neural network potentials. MIT MD rep-learn transformer pre-trained
• DIG: Dive into Graphs (🥈21 · ⭐ 1.7K · 📉) - A library for graph deep learning research. GPL-3.0
• mlcolvar (🥈16 · ⭐ 74 · 📉) - A unified framework for machine learning collective variables for enhanced sampling simulations. MIT enhanced-sampling

➕ Added Projects

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

• pymatviz (🥉17 · ⭐ 78 · ➕) - A toolkit for visualizations in materials informatics. MIT general-tool probabilistic
• FAENet (🥈11 · ⭐ 21 · ➕) - MIT
• GNoME Explorer (🥉7 · ⭐ 500 · 🐣) - Graph Networks for Materials Exploration Database. Apache-2 datasets materials-discovery
• Materials Discovery: GNoME (🥈6 · ⭐ 500 · 🐣) - Apache-2 r e p - l e a r n , d a t a s e t s
• halex (🥉2 · ⭐ 1 · 🐣) - Hamiltonian Learning for Excited States https://doi.org/10.48550/arXiv.2311.00844. Unlicensed ML-WFT excited-states
• TorchMD-NET (🥈20 · ⭐ 220 · ➕) - Neural network potentials based on graph neural networks and equivariant transformers. MIT ML-IAP rep-learn tranformer pre-trained
• LLM-Prop (🥉8 · ⭐ 4 · ➕) - A repository for the LLM-Prop implementation. None found
• MLXDM (🥉7 · ⭐ 4 · 💤) - A Neural Network Potential with Rigorous Treatment of Long-Range Dispersion https://doi.org/10.1039/D2DD00150K. MIT long-range
• paper-data-redundancy (🥉7 · ⭐ 3 · 🐣) - Codes and data for the paper On the redundancy in large material datasets: efficient and robust learning with less data. BSD-3 small-data single-paper
• paper-ml-robustness-material-property (🥉4 · ⭐ 3 · 💤) - BSD-3 d a t a s e t s , s i n g l e - p a p e r
• Materials Data Facility (MDF) (🥈9 · ⭐ 10 · 💤) - A simple way to publish, discover, and access materials datasets. Publication of very large datasets supported (e.g.,.. Apache-2
• OPTIMADE Python tools (🥇25 · ⭐ 54 · ➕) - Tools for implementing and consuming OPTIMADE APIs in Python. MIT
• OPTIMADE Tutorial Exercises (🥈8 · ⭐ 11 · ➕) - Tutorial exercises for the OPTIMADE API. MIT datasets
• optimade.science (🥉8 · ⭐ 8 · ➕) - A sky-scanner Optimade browser-only GUI. MIT datasets
• Does this material exist? (🥉4 · ⭐ 2 · ➕) - Vote on whether you think predicted crystal structures could be synthesised. MIT for-fun materials-discovery
• OPTIMADE providers dashboard (🥉4 · ⭐ 1 · ➕) - A dashboard of known providers. Unlicensed
• GPUMD (🥇20 · ⭐ 300 · ➕) - GPUMD is a highly efficient general-purpose molecular dynamic (MD) package and enables machine-learned potentials.. GPL-3.0 MD C++ electrostatics
• nep-data (🥉1 · ⭐ 9 · 💀) - Data related to the NEP machine-learned potential of GPUMD. Unlicensed ML-IAP MD transport-phenomena

v2023.12.25

Test whether Zenodo latest release DOI 10.5281/zenodo.10430261 is working. That DOI is used in the README DOI badge.

v2023.12.21

Release for Zenodo DOI.

Update: 2023.12.03-21.16

➕ Added Projects

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

• Open Databases Integration for Materials Design (OPTIMADE) (🥈17 · ⭐ 59 · ➕) - Specification of a common REST API for access to materials databases. CC-BY-4.0
• MODNet (🥇17 · ⭐ 53 · ➕) - MODNet: a framework for machine learning materials properties. MIT pre-trained small-data transfer-learning
• Metatensor (🥉15 · ⭐ 25 · ➕) - Storage format for equivariant atomistic machine learning. BSD-3
• mlcolvar (🥈16 · ⭐ 59 · ➕) - A unified framework for machine learning collective variables for enhanced sampling simulations. MIT enhanced-sampling
• JAX-DFT (🥇25 · ⭐ 32K · ➕) - Google Research. Apache-2
• DIG: Dive into Graphs (🥈21 · ⭐ 1.7K · ➕) - A library for graph deep learning research. GPL-3.0
• ATOM3D (🥇18 · ⭐ 280 · 💤) - ATOM3D: tasks on molecules in three dimensions. MIT biomolecules benchmarking
• ChemCrow (🥇17 · ⭐ 320 · 🐣) - Chemcrow. MIT
• ChemDataExtractor (🥈16 · ⭐ 270 · 💀) - Automatically extract chemical information from scientific documents. MIT literature-data
• ChemNLP project (🥈16 · ⭐ 110 · ➕) - ChemNLP project. MIT datasets
• GT4SD - Generative Toolkit for Scientific Discovery (🥈15 · ⭐ 280 · ➕) - Gradio apps of generative models in GT4SD. MIT generative pre-trained drug-discovery
• dlpack (🥉14 · ⭐ 800 · 💤) - common in-memory tensor structure. Apache-2 C++
• Geometric GNN Dojo (🥇12 · ⭐ 350 · ➕) - New to geometric GNNs: try our practical notebook, prepared for MPhil students at the University of Cambridge. MIT rep-learn
• QH9: A Quantum Hamiltonian Prediction Benchmark (🥈12 · ⭐ 280 · ➕) - Artificial Intelligence for Science (AIRS). CC-BY-NC-SA 4.0 ML-DFT
• QHNet (🥈12 · ⭐ 280 · ➕) - Artificial Intelligence for Science (AIRS). GPL-3.0 rep-learn
• Grad DFT (🥈12 · ⭐ 43 · ➕) - Grad-DFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation.. Apache-2
• pretrained-gnns (🥇10 · ⭐ 870 · ➕) - Strategies for Pre-training Graph Neural Networks. MIT pre-trained
• DSECOP (🥈10 · ⭐ 31 · ➕) - This repository contains data science educational materials developed by DSECOP Fellows. CCO-1.0
• pair_nequip (🥉10 · ⭐ 29 · 💀) - LAMMPS pair style for NequIP. MIT ML-IAP rep-learn
• tinker-hp (🥉9 · ⭐ 69 · ➕) - Tinker-HP: High-Performance Massively Parallel Evolution of Tinker on CPUs & GPUs. Custom
• lie-nn (🥈9 · ⭐ 22 · ➕) - Tools for building equivariant polynomials on reductive Lie groups. MIT rep-learn
• TurboGAP (🥉9 · ⭐ 14 · ➕) - The TurboGAP code. Custom Fortran
• MoLFormers UI (🥉8 · ⭐ 140 · ➕) - Repository for MolFormer. Apache-2 transformer Language models pre-trained drug-discovery
• MoLFormer (🥉8 · ⭐ 140 · ➕) - Repository for MolFormer. Apache-2 transformer pre-trained drug-discovery
• pair_allegro (🥉8 · ⭐ 26 · ➕) - LAMMPS pair style for Allegro deep learning interatomic potentials with parallelization support. MIT ML-IAP rep-learn
• chemlift (🥉8 · ⭐ 10 · 🐣) - Language-interfaced fine-tuning for chemistry. MIT
• T-e3nn (🥉8 · ⭐ 6 · 💤) - Time-reversal Euclidean neural networks based on e3nn. MIT magnetism
• Awesome Neural Geometry (🥉7 · ⭐ 780 · ➕) - A curated collection of resources and research related to the geometry of representations in the brain, deep networks,.. Unlicensed educational rep-learn
• COATI (🥉6 · ⭐ 59 · 🐣) - COATI: multi-modal contrastive pre-training for representing and traversing chemical space. Apache-2 drug-discovery pre-trained rep-learn
• Mat2Spec (🥉6 · ⭐ 24 · 💀) - MIT spectroscopy
• NequIP-JAX (🥉5 · ⭐ 10 · ➕) - JAX implementation of the NequIP interatomic potential. Unlicensed
• MAPI_LLM (🥉5 · ⭐ 4 · ➕) - A LLM application developed during the LLM March MADNESS Hackathon https://doi.org/10.1039/D3DD00113J. MIT dataset
• soap_turbo (🥉5 · ⭐ 4 · 💤) - soap_turbo comprises a series of libraries to be used in combination with QUIP/GAP and TurboGAP. Custom Fortran
• MACE-tutorials (🥉5 · ⭐ 3 · 🐣) - Another set of tutorials for the MACE interatomic potential by one of the authors. MIT ML-IAP rep-learn MD
• Point Edge Transformer (PET) (🥉5 · ➕) -...

Update: 2023.08.25-14.45

➕ Added Projects

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

• MLDensity_tutorial (🥉1 · ⭐ 3 · 🐣) - Tutorial files to work with ML for the charge density in molecules and solids. ❗Unlicensed
• KFAC-JAX (🥇26 · ⭐ 10K · ➕) - Open source code for AlphaFold. Apache-2
• AlphaFold (🥇24 · ⭐ 10K · ➕) - Open source code for AlphaFold. Apache-2
• DM21 (🥇21 · ⭐ 12K · ➕) - This package provides a PySCF interface to the DM21 (DeepMind 21) family of exchange-correlation functionals described.. Apache-2
• DeepQMC (🥇20 · ⭐ 280 · ➕) - Deep learning quantum Monte Carlo for electrons in real space. MIT
• FermiNet (🥈15 · ⭐ 550 · ➕) - An implementation of the Fermionic Neural Network for ab-initio electronic structure calculations. Apache-2
• GElib (🥉9 · ⭐ 15 · ➕) - C++/CUDA library for SO(3) equivariant operations. MPL-2.0
• Cormorant (🥉6 · ⭐ 51 · 💀) - Codebase for Cormorant Neural Networks. Unlicensed
• Autobahn (🥉5 · ⭐ 26 · 💀) - Repository for Autobahn: Automorphism Based Graph Neural Networks. MIT
• SphericalNet ( ⭐ 2 · 💤) - Implementation of Clebsch-Gordan Networks (CGnet: https://arxiv.org/pdf/1806.09231.pdf) by GElib & cnine libraries in.. Unlicensed
• cnine (➕) - Unlicensed
• chemrev-gpr (🥉4 · ⭐ 5 · 💀) - Notebooks accompanying the paper on GPR in materials and molecules in Chemical Reviews 2020. Unlicensed
• paper-qa (🥇23 · ⭐ 2.6K · 🐣) - LLM Chain for answering questions from documents with citations. Apache-2
• Best-of Machine Learning with Python (🥇22 · ⭐ 14K · ➕) - A ranked list of awesome machine learning Python libraries. Updated weekly. CC-BY-4.0 general-ml Python
• Graph-based Deep Learning Literature (🥈18 · ⭐ 4.3K · ➕) - links to conference publications in graph-based deep learning. MIT general-ml rep-learn
• Awesome Materials Informatics (🥉11 · ⭐ 290 · ➕) - Curated list of known efforts in materials informatics = modern materials science. Custom t o p i c s / m a t e r i a l s - i n f o r m a t i c s
• The Collection of Database and Dataset Resources in Materials Science (🥉8 · ⭐ 160 · ➕) - A list of databases, datasets and books/handbooks where you can find materials properties for machine learning.. Unlicensed datasets
• A Highly Opinionated List of Open-Source Materials Informatics Resources (🥉7 · ⭐ 93 · 💀) - A Highly Opinionated List of Open Source Materials Informatics Resources. MIT
• GitHub topic materials-informatics (➕) - Unlicensed
• cdk (🥇25 · ⭐ 430 · ➕) - The Chemistry Development Kit. LGPL-2.1 cheminformatics Java
• MPContribs (🥇23 · ⭐ 32 · ➕) - Platform for materials scientists to contribute and disseminate their materials data through Materials Project. MIT
• Open Catalyst datasets (🥇18 · ⭐ 450 · ➕) - The datasets of the Open Catalyst project, OC20, OC22. CC-BY-4.0
• GT4SD (🥇18 · ⭐ 230 · ➕) - GT4SD, an open-source library to accelerate hypothesis generation in the scientific discovery process. MIT pre-trained drug-discovery rep-learn
• CHGNet (🥈18 · ⭐ 79 · 🐣) - Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov. Custom MD pre-trained electrostatics magnetism structure-relaxation
• escnn (🥈17 · ⭐ 200 · ➕) - Equivariant Steerable CNNs Library for Pytorch https://quva-lab.github.io/escnn/. Custom
• MatBench (🥈16 · ⭐ 77 · ➕) - Matbench: Benchmarks for materials science property prediction. MIT datasets benchmarking
• NNPOps (🥈15 · ⭐ 61 · ➕) - High-performance operations for neural network potentials. MIT MD C++
• AI for Science Resources (🥉14 · ⭐ 220 · 🐣) - List of resources for AI4Science research, including learning resources. GPL-3.0 license
• Artificial Intelligence for Science (AIRS) (🥉14 · ⭐ 220 · 🐣) - Artificial Intelligence for Science (AIRS). GPL-3.0 license rep-learn generative MLIAP MD ML-DFT ML-WFT biomolecules
• openmm-torch (🥈14 · ⭐ 130 · ➕) - OpenMM plugin to define forces with neural networks. Custom MLIAP C++
• SPICE (🥈14 · ⭐ 89 · ➕) - A collection of QM data for training potential functions. MIT MLIAP MD
• mp-pyrho (🥉14 · ⭐ 27 · ➕) - Custom ML-DFT
• GlassPy (🥈13 · ⭐ 14 · ➕) - Python module for scientists working with glass materials. GPL-3.0
• mat2vec (🥈12 · ⭐ 590 · ➕) - Supplementary Materials for Tshitoyan et al. Unsupervised word embeddings capture latent knowledge from ...

Update: 2023.06.12-20.27

➕ Added Projects

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

• Deep Graph Library (DGL) (🥇37 · ⭐ 12K · ➕) - Python package built to ease deep learning on graph,.. Apache-2
• DeepChem (🥇36 · ⭐ 4.4K · ➕) - Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry,.. MIT
• RDKit (🥇30 · ⭐ 2.1K · ➕) - BSD-3
• DeePMD-kit (🥇28 · ⭐ 1.1K · ➕) - A deep learning package for many-body potential.. ❗️LGPL-3.0
• Matminer (🥇27 · ⭐ 390 · ➕) - Data mining for materials science. ❗Unlicensed
• SchNetPack (🥇25 · ⭐ 600 · ➕) - SchNetPack - Deep Neural Networks for Atomistic Systems. ❗Unlicensed
• DScribe (🥇25 · ⭐ 320 · ➕) - DScribe is a python package for creating machine learning.. Apache-2
• QUIP (🥈25 · ⭐ 290 · ➕) - libAtoms/QUIP molecular dynamics framework:.. ❗Unlicensed
• paper-qa (🥇24 · ⭐ 2.6K · 🐣) - LLM Chain for answering questions from documents with citations. Apache-2
• e3nn (🥇23 · ⭐ 680 · ➕) - A modular framework for neural networks with Euclidean symmetry. ❗Unlicensed
• dgl-lifesci (🥇23 · ⭐ 580 · ➕) - Python package for graph neural networks in chemistry and.. Apache-2
• MEGNet (🥇22 · ⭐ 450 · ➕) - Graph Networks as a Universal Machine Learning Framework for.. BSD-3
• DP-GEN (🥇22 · ⭐ 220 · ➕) - The deep potential generator to generate a deep-learning.. ❗️LGPL-3.0
• dpdata (🥇22 · ⭐ 130 · ➕) - Manipulating multiple atomic simulation data formats, including.. ❗️LGPL-3.0
• kgcnn (🥈22 · ⭐ 75 · ➕) - Graph convolution with tf.keras. MIT
• NVIDIA Deep Learning Examples for Tensor Cores (🥇21 · ⭐ 11K · ➕) - State-of-the-Art Deep Learning scripts organized by.. ❗Unlicensed
• TorchANI (🥇21 · ⭐ 390 · ➕) - Accurate Neural Network Potential on PyTorch. MIT
• MAML (🥈21 · ⭐ 240 · ➕) - Python for Materials Machine Learning, Materials Descriptors, Machine.. BSD-3
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