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Recent Releases of best-of-atomistic-machine-learning

best-of-atomistic-machine-learning - Update: 2025.04.09-13.10

📉 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.

  • CHGNet (🥈19 · ⭐ 290 · 📉) - Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov. Custom ML-IAP MD pretrained electrostatics magnetism structure-relaxation
  • Scikit-Matter (🥉15 · ⭐ 81 · 📉) - A collection of scikit-learn compatible utilities that implement methods born out of the materials science and.. BSD-3 scikit-learn


Published by github-actions[bot] about 1 year ago

best-of-atomistic-machine-learning - Update: 2025.04.09

📈 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.

  • KLIFF (🥈18 · ⭐ 35 · 📈) - KIM-based Learning-Integrated Fitting Framework for interatomic potentials. LGPL-2.1 probabilistic workflows
  • ChemCrow (🥈16 · ⭐ 730 · 📈) - Open source package for the accurate solution of reasoning-intensive chemical tasks. MIT ai-agent
  • TorchSim (🥈16 · ⭐ 170 · 🐣) - Torch-native, batchable, atomistic simulation. MIT HTC UIP ML-IAP structure-optimization
  • hippynn (🥈13 · ⭐ 76 · 📈) - python library for atomistic machine learning. Custom workflows
  • dftio (🥈8 · ⭐ 8 · 📈) - dftio is to assist machine learning communities to transcript DFT output into a format that is easy to read or used by.. LGPL-3.0 data-structures workflows

📉 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.

  • MODNet (🥇16 · ⭐ 91 · 📉) - MODNet: a framework for machine learning materials properties. MIT pretrained small-data transfer-learning

➕ Added Projects

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


Published by github-actions[bot] about 1 year ago

best-of-atomistic-machine-learning - Update: 2025.04.08

📈 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.

📉 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.

  • M3GNet (🥉18 · ⭐ 280 · 📉) - Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art.. BSD-3 ML-IAP pretrained
  • HamGNN (🥈7 · ⭐ 91 · 📉) - An E(3) equivariant Graph Neural Network for predicting electronic Hamiltonian matrix. GPL-3.0 rep-learn magnetism C-lang

➕ Added Projects

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

  • DeePTB (🥇15 · ⭐ 71 · ➕) - DeePTB: A deep learning package for tight-binding approach with ab initio accuracy. LGPL-3.0 ML-DFT
  • DP-GEN2 (🥈14 · ⭐ 38 · ➕) - 2nd generation of the Deep Potential GENerator. LGPL-3.0 ML-IAP MD workflows
  • DeepModeling Projects (🥈10 · ⭐ 6 · ➕) - DeepModeling projects. CC-BY-4.0
  • DeepMD-GNN (🥉9 · ⭐ 39 · ➕) - DeePMD-kit plugin for various graph neural network models. LGPL-3.0 rep-learn MD UIP C++
  • DeepModeling Tutorials (🥉7 · ⭐ 15 · ➕) - Tutorials for DeepModeling projects. Unlicensed
  • dftio (🥉6 · ⭐ 8 · ➕) - dftio is to assist machine learning communities to transcript DFT output into a format that is easy to read or used by.. LGPL-3.0 data-structures workflows


Published by github-actions[bot] about 1 year ago

best-of-atomistic-machine-learning - Update: 2025.04.07-07.33

📈 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.

📉 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.


Published by github-actions[bot] about 1 year ago

best-of-atomistic-machine-learning - Update: 2025.04.07

📈 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.

  • pymatviz (🥇23 · ⭐ 200 · 📈) - A toolkit for visualizations in materials informatics. MIT general-tool probabilistic
  • exmol (🥇22 · ⭐ 330 · 📈) - Explainer for black box models that predict molecule properties. MIT
  • TorchSim (🥉13 · ⭐ 140 · 🐣) - Torch-native, batchable, atomistic simulation. MIT HTC UIP ML-IAP structure-optimization
  • DeepErwin (🥉9 · ⭐ 54 · 📈) - DeepErwin is a python 3.8+ package that implements and optimizes JAX 2.x wave function models for numerical solutions.. Custom

📉 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.

  • FLARE (🥇18 · ⭐ 310 · 📉) - An open-source Python package for creating fast and accurate interatomic potentials. MIT C++ ML-IAP
  • SpheriCart (🥇18 · ⭐ 83 · 📉) - Multi-language library for the calculation of spherical harmonics in Cartesian coordinates. MIT
  • gptchem (🥈12 · ⭐ 250 · 💀) - Use GPT-3 to solve chemistry problems. MIT
  • PiNN (🥈12 · ⭐ 110 · 📉) - A Python library for building atomic neural networks. BSD-3
  • BenchML (🥉11 · ⭐ 15 · 💀) - ML benchmarking and pipeling framework. Apache-2 benchmarking

➕ Added Projects

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

  • SMACT (🥇27 · ⭐ 110 · ➕) - Python package to aid materials design and informatics. MIT HTC structure-prediction electrostatics
  • MACE-FOUNDATION models (🥉19 · ⭐ 640 · ➕) - MACE-MP models. MIT ML-IAP pretrained rep-learn MD
  • AtomAI (🥈19 · ⭐ 210 · 💀) - Deep and Machine Learning for Microscopy. MIT computer-vision USL experimental-data
  • ElementEmbeddings (🥈16 · ⭐ 41 · ➕) - Python package to interact with high-dimensional representations of the chemical elements. MIT XAI USL viz
  • pySIPFENN (🥈16 · ⭐ 22 · ➕) - Python python toolset for Structure-Informed Property and Feature Engineering with Neural Networks. It offers unique.. LGPL-3.0 material-defect Disordered Materials pretrained transfer-learning
  • ChemML (🥈15 · ⭐ 160 · ➕) - ChemML is a machine learning and informatics program suite for the chemical and materials sciences. BSD-3 cheminformatics active-learning workflows
  • SLICES and MatterGPT (🥇15 · ⭐ 100 · ➕) - SLICES: An Invertible, Invariant, and String-based Crystal Representation [2023, Nature Communications] MatterGPT,.. LGPL-2.1 rep-eng language-models transformer materials-discovery structure-prediction
  • xtal2png (🥈14 · ⭐ 37 · 💀) - Encode/decode a crystal structure to/from a grayscale PNG image for direct use with image-based machine learning.. MIT computer-vision
  • Bgolearn (🥈13 · ⭐ 91 · ➕) - [Materials & Design 2024] A Bayesian global optimization package for material design Adaptive Learning | Active.. MIT materials-discovery probabilistic
  • matdiscover (🥈13 · ⭐ 41 · 💤) - A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces. MIT <a href="https://www.psik2022.net/program/symposia#h.phM6hJbQD9dex">materials-discovery rep-eng HTC
  • Awesome-Scientific-Language-Models (🥈11 · ⭐ 560 · ➕) - A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery (EMNLP24). MIT language-models general-ml pretrained multimodal
  • nablaDFT (🥈11 · ⭐ 200 · ➕) - nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset. MIT ML-DFT ML-WFT drug-discovery ML-IAP benchmarking
  • PDynA (🥉11 · ⭐ 41 · ➕) - Python package to analyse the structural dynamics of perovskites. MIT MD
  • pumml (🥈11 · ⭐ 37 · 💀) - Positive and Unlabeled Materials Machine Learning (pumml) is a code that uses semi-supervised machine learning to.. MIT materials-discovery
  • MPDS API (🥈11 · ⭐ 27 · ➕) - Tutorials, notebooks, issue tracker, and website on the MPDS API: the data retrieval interface for the Materials.. CC-BY-4.0 community-resource literature-data
  • MLforMaterials (🥉7 · ⭐ 79 · ➕) - Online resource for a practical course in machine learning for materials research at Imperial College London.. MIT community-resource general-ml rep-eng materials-discovery
  • molecular-vae (🥉7 · ⭐ 65 · 💀) - Pytorch implementation of the paper Automatic Chemical Design Using a Data-Driven Continuous Representation of.. MIT rep-learn cheminformatics single-paper
  • PolyGNN (🥉7 · ⭐ 38 · ➕) - polyGNN is a Python library to automate ML model training for polymer informatics. MIT soft-matter multitask single-paper
  • BPNET (🥉7 · ⭐ 2 · 🐣) - Behler-Parrinello type neural networks in Fortran2008. MIT rep-eng Fortran
  • Geom3D (🥉6 · ⭐ 120 · 💀) - Geom3D: Geometric Modeling on 3D Structures, NeurIPS 2023. MIT benchmarking single-paper
  • LLM4Chem (🥉6 · ⭐ 81 · 💤) - Official code repo for the paper LlaSMol: Advancing Large Language Models for Chemistry with a Large-Scale,.. MIT cheminformatics datasets
  • Graph-Aware-Transformers (🥉6 · ⭐ 56 · 🐣) - Graph-Aware Attention for Adaptive Dynamics in Transformers. Apache-2 transformer graph-data pretrained single-paper
  • ffonons (🥉6 · ⭐ 18 · ➕) - Phonons from ML force fields. MIT benchmarking density-of-states
  • polyVERSE (🥉6 · ⭐ 17 · ➕) - polyVERSE is a comprehensive repository of informatics-ready datasets curated by the Ramprasad Group. Custom soft-matter
  • Crystalformer (🥉5 · ⭐ 17 · ➕) - The official code respository for Crystalformer: Infinitely Connected Attention for Periodic Structure Encoding (ICLR.. MIT transformer single-paper
  • thermo (🥇5 · ⭐ 16 · 💤) - Data-driven risk-conscious thermoelectric materials discovery. MIT materials-discovery experimental-data active-learning transport-phenomena
  • MUSE (🥉5 · ⭐ 4 · ➕) - A python package for fast building amorphous solids and liquid mixtures from @materialsproject computed structures and.. MIT ML-IAP Disordered Materials
  • 3D-EMGP (🥉4 · ⭐ 34 · 💤) - [AAAI 2023] The implementation for the paper Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs. MIT pretrained rep-learn single-paper
  • Crystalframer (🥉4 · ⭐ 5 · 🐣) - The official code respository for Rethinking the role of frames for SE(3)-invariant crystal structure modeling (ICLR.. MIT transformer single-paper


Published by github-actions[bot] about 1 year ago

best-of-atomistic-machine-learning - Update: 2025.01.02

📈 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.

  • dgl-lifesci (🥇24 · ⭐ 740 · 💀) - Python package for graph neural networks in chemistry and biology. Apache-2
  • ChemCrow (🥇18 · ⭐ 660 · 📈) - Open source package for the accurate solution of reasoning-intensive chemical tasks. MIT ai-agent
  • GT4SD (🥇18 · ⭐ 340 · 📈) - GT4SD, an open-source library to accelerate hypothesis generation in the scientific discovery process. MIT pretrained drug-discovery rep-learn
  • Orb Models (🥈18 · ⭐ 220 · 🐣) - ORB forcefield models from Orbital Materials. Custom ML-IAP pretrained
  • Rascaline (🥇16 · ⭐ 49 · 📈) - Computing representations for atomistic machine learning. BSD-3 Rust C++

📉 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.

  • FAIR Chemistry datasets (🥇25 · ⭐ 940 · 📉) - Datasets OC20, OC22, etc. Formerly known as Open Catalyst Project. MIT catalysis
  • MPContribs (🥇22 · ⭐ 37 · 📉) - Platform for materials scientists to contribute and disseminate their materials data through Materials Project. MIT
  • DeepQMC (🥇20 · ⭐ 360 · 📉) - Deep learning quantum Monte Carlo for electrons in real space. MIT
  • tinker-hp (🥉9 · ⭐ 82 · 📉) - Tinker-HP: High-Performance Massively Parallel Evolution of Tinker on CPUs & GPUs. Custom
  • fplib (🥉8 · ⭐ 7 · 📉) - libfp is a library for calculating crystalline fingerprints and measuring similarities of materials. MIT C-lang single-paper

➕ Added Projects

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


Published by github-actions[bot] over 1 year ago

best-of-atomistic-machine-learning - Update: 2024.08.19-13.22

Removed category biomolecules in accordance with issue #125.


Published by github-actions[bot] almost 2 years ago

best-of-atomistic-machine-learning - 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.

➕ 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. MIT rep-learn
  • ML for catalysis tutorials (🥉6 · ⭐ 8 · 💀) - A jupyter book repo for tutorial on how to use OCP ML models for catalysis. MIT
  • Cephalo (🥉6 · ⭐ 5 · 🐣) - Multimodal Vision-Language Models for Bio-Inspired Materials Analysis and Design. Apache-2 generative multimodal pretrained
  • KSR-DFT (🥇6 · ⭐ 4 · 💀) - Kohn-Sham regularizer for machine-learned DFT functionals. Apache-2
  • ACEpsi.jl (🥉6 · ⭐ 2 · 💤) - ACE wave function parameterizations. MIT rep-eng Julia
  • crystal-text-llm (🥉5 · ⭐ 63 · 🐣) - Large language models to generate stable crystals. CC-BY-NC-4.0 materials-discovery
  • The Perovskite Database Project (🥉5 · ⭐ 58 · ➕) - Perovskite Database Project aims at making all perovskite device data, both past and future, available in a form.. Unlicensed community-resource
  • Joint Multidomain Pre-Training (JMP) (🥉5 · ⭐ 32 · 🐣) - Code for From Molecules to Materials Pre-training Large Generalizable Models for Atomic Property Prediction. CC-BY-NC-4.0 pretrained ML-IAP general-tool
  • QMLearn (🥈5 · ⭐ 11 · 💀) - Quantum Machine Learning by learning one-body reduced density matrices in the AO basis... MIT
  • InfGCN for Electron Density Estimation (🥉5 · ⭐ 10 · 💤) - Official implementation of the NeurIPS 23 spotlight paper of InfGCN. MIT rep-learn
  • GN-MM (🥉5 · ⭐ 10 · 💀) - The Gaussian Moment Neural Network (GM-NN) package developed for large-scale atomistic simulations employing atomistic.. MIT active-learning MD rep-eng magnetism
  • EGraFFBench (🥉5 · ⭐ 8 · 💤) - Unlicensed single-paper benchmarking ML-IAP
  • GDB-9-Ex9 and ORNL_AISD-Ex (🥉5 · ⭐ 6 · 💤) - Distributed computing workflow for generation and analysis of large scale molecular datasets obtained running multi-.. Unlicensed
  • MXenes4HER (🥉5 · ⭐ 5 · 💀) - Predicting hydrogen evolution (HER) activity over 4500 MXene materials https://doi.org/10.1039/D3TA00344B. GPL-3.0 materials-discovery catalysis scikit-learn single-paper
  • Geometric-GNNs (🥉4 · ⭐ 85 · ➕) - List of Geometric GNNs for 3D atomic systems. Unlicensed datasets educational rep-learn
  • MAGUS (🥉4 · ⭐ 56 · 💀) - Machine learning And Graph theory assisted Universal structure Searcher. Unlicensed structure-prediction active-learning
  • Allegro-Legato (🥉4 · ⭐ 19 · 💤) - An extension of Allegro with enhanced robustness and time-to-failure. MIT MD
  • Mapping out phase diagrams with generative classifiers (🥉4 · ⭐ 7 · 💀) - Repository for our ``Mapping out phase diagrams with generative models paper. MIT phase-transition
  • automl-materials (🥉4 · ⭐ 5 · 💀) - AutoML for Regression Tasks on Small Tabular Data in Materials Design. MIT autoML benchmarking single-paper
  • ML-atomate (🥉4 · ⭐ 3 · 💤) - Machine learning-assisted Atomate code for autonomous computational materials screening. GPL-3.0 active-learning workflows
  • AI4ChemMat Hands-On Series (🥉4 · ⭐ 1 · ➕) - Hands-On Series organized by Chemistry and Materials working group at Argonne Nat Lab. MPL-2.0
  • ALEBREW (🥉3 · ⭐ 9 · 🐣) - Official repository for the paper Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic.. Custom ML-IAP MD
  • PyFLAME (🥉3 · 💀) - An automated approach for developing neural network interatomic potentials with FLAME.. Unlicensed active-learning structure-prediction structure-optimization rep-eng Fortran
  • tmQMwB97MV Dataset (🥉2 · ⭐ 5 · ➕) - Code for Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQMwB97MV.. Unlicensed catalysis rep-learn
  • AisNet (🥉2 · ⭐ 3 · 💀) - A Universal Interatomic Potential Neural Network with Encoded Local Environment Features.. MIT
  • nnp-pre-training (🥉1 · ⭐ 6 · 💤) - Synthetic pre-training for neural-network interatomic potentials. Unlicensed pretrained MD
  • mag-ace (🥉1 · ⭐ 2 · 💤) - Magnetic ACE potential. FORTRAN interface for LAMMPS SPIN package. Unlicensed magnetism MD Fortran


Published by github-actions[bot] almost 2 years ago

best-of-atomistic-machine-learning - 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.


Published by github-actions[bot] almost 2 years ago

best-of-atomistic-machine-learning - 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


Published by github-actions[bot] almost 2 years ago

best-of-atomistic-machine-learning - 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.

📉 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.

➕ 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


Published by github-actions[bot] almost 2 years ago

best-of-atomistic-machine-learning - 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
  • pairnequip (🥉10 · ⭐ 29 · 💀) - LAMMPS pair style for NequIP. MIT ML-IAP <a href="https://en.wikipedia.org/wiki/Featurelearning">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
  • pairallegro (🥉8 · ⭐ 26 · ➕) - LAMMPS pair style for Allegro deep learning interatomic potentials with parallelization support. MIT ML-IAP <a href="https://en.wikipedia.org/wiki/Featurelearning">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
  • soapturbo (🥉5 · ⭐ 4 · 💤) - soapturbo 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 · ➕) - Point Edge Transformer. Unlicensed rep-learn transformer
  • ChemDataWriter (🥉4 · ⭐ 8 · 🐣) - ChemDataWriter is a transformer-based library for automatically generating research books in the chemistry area. MIT literature-data
  • torch_spex (🥉4 · ➕) - Spherical expansions in PyTorch. Unlicensed
  • PeriodicPotentials (🥉4 · 💀) - A Periodic table app that displays potentials based on the selected elements. MIT community-resource viz JavaScript
  • SciBot (🥉3 · ⭐ 14 · 🐣) - SciBot is a simple demo of building a domain-specific chatbot for science. Unlicensed
  • CatBERTa (🥉3 · ⭐ 13 · ➕) - Large Language Model for Catalyst Property Prediction. Unlicensed transformer catalysis
  • A3MD (🥉2 · ⭐ 5 · 💀) - MPNN-like + Analytic Density Model = Accurate electron densities. Unlicensed representation-learning single-paper
  • LAMMPS-style pair potentials with GAP (🥉2 · ⭐ 3 · 💀) - A tutorial on how to create LAMMPS-style pair potentials and use them in combination with GAP potentials to run MD.. Unlicensed ML-IAP MD rep-eng
  • MEGNetSparse (🥉2 · ⭐ 1 · 🐣) - A library imlementing a graph neural network with sparse representation from Code for Kazeev, N., Al-Maeeni, A.R.,.. MIT material-defect
  • Allegro-JAX (🥉1 · ⭐ 11 · 🐣) - JAX implementation of the Allegro interatomic potential. Unlicensed
  • APET (🥉1 · ⭐ 2 · ➕) - Atomic Positional Embedding-based Transformer. GPL-3.0 density-of-states transformer
  • mlp (🥉1 · ⭐ 1 · 💀) - Proper orthogonal descriptors for efficient and accurate interatomic potentials... Unlicensed Julia


Published by github-actions[bot] almost 2 years ago

best-of-atomistic-machine-learning - 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 materials.. MIT rep-learn
  • TensorMol (🥈12 · ⭐ 260 · 💀) - Tensorflow + Molecules = TensorMol. GPL-3.0 single-paper
  • OpenMM-ML (🥉10 · ⭐ 50 · ➕) - High level API for using machine learning models in OpenMM simulations. MIT MLIAP
  • ai4materialdesign (🥈10 · ⭐ 1 · ➕) - Code for Kazeev, N., Al-Maeeni, A.R., Romanov, I. et al. Sparse representation for machine learning the properties of.. Apache-2 pre-trained <a href="https://en.wikipedia.org/wiki/Crystallographicdefect">material-defect
  • EDM (🥉9 · ⭐ 290 · 💀) - E(3) Equivariant Diffusion Model for Molecule Generation in 3D. MIT
  • PROPhet (🥈9 · ⭐ 59 · 💀) - PROPhet is a code to integrate machine learning techniques with first-principles quantum chemistry approaches. GPL-3.0 MLIAP MD single-paper C++
  • escnnjax (🥉8 · ⭐ 21 · 🐣) - Equivariant Steerable CNNs Library for Pytorch https://quva-lab.github.io/escnn/. <a href="https://github.com/emilemathieu/escnnjax/blob/master/LICENSE">Custom
  • SkipAtom (🥈8 · ⭐ 21 · 💀) - Distributed representations of atoms, inspired by the Skip-gram model. MIT
  • wfl (🥉8 · ⭐ 13 · ➕) - Workflow is a Python toolkit for building interatomic potential creation and atomistic simulation workflows. Unlicensed workflows HTC
  • EquiformerV2 (🥉6 · ⭐ 62 · 🐣) - [arXiv23] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations. MIT
  • MEGAN (🥈6 · ⭐ 1 · ➕) - Minimal implementation of graph attention student model architecture. MIT XAI rep-learn
  • tensorfieldnetworks (🥉5 · ⭐ 140 · 💀) - MIT
  • EquivariantOperators.jl (🥉5 · ⭐ 17 · 💤) - MIT Julia
  • SciGlass (🥉5 · ⭐ 6 · ➕) - The database contains a vast set of data on the properties of glass materials. MIT
  • CraTENet (🥉5 · ⭐ 6 · ➕) - An attention-based deep neural network for thermoelectric transport properties. MIT transport-phenomena
  • closed-loop-acceleration-benchmarks (🥈5 · ➕) - Data and scripts in support of the publication By how much can closed-loop frameworks accelerate computational.. MIT materials-discovery active-learning single-paper
  • Closed-loop acceleration benchmarks (🥈5 · ➕) - Data and scripts in support of the publication By how much can closed-loop frameworks accelerate computational.. MIT materials-discovery active-learning single-paper
  • ML-for-CurieTemp-Predictions (🥉5 · 🐣) - Machine Learning Predictions of High-Curie-Temperature Materials. MIT single-paper magnetism
  • Linear vs blackbox (🥉4 · 💤) - Code and data related to the publication: Interpretable models for extrapolation in scientific machine learning. MIT XAI single-paper rep-eng
  • Atom2Vec (🥉3 · ⭐ 24 · 💀) - Atom2Vec: a simple way to describe atoms for machine learning. Unlicensed
  • sldiscovery (🥉3 · ⭐ 5 · 💤) - Data processing and models related to Quantifying the performance of machine learning models in materials discovery. Apache-2 <a href="https://www.psik2022.net/program/symposia#h.phM6hJbQD9dex">materials-discovery single-paper
  • Element encoder (🥉3 · ⭐ 5 · 💀) - Autoencoder neural network to compress properties of atomic species into a vector representation. GPL-3.0 single-paper
  • DeepCDP (🥉3 · ⭐ 2 · ➕) - DeepCDP: Deep learning Charge Density Prediction. Unlicensed
  • MateriApps (➕) - Unlicensed


Published by github-actions[bot] almost 2 years ago

best-of-atomistic-machine-learning - 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
  • NequIP (🥇20 · ⭐ 390 · ➕) - NequIP is a code for building E(3)-equivariant interatomic potentials. MIT
  • JARVIS-Tools (🥈20 · ⭐ 220 · ➕) - JARVIS-Tools: an open-source software package for.. ❗Unlicensed
  • ocp (🥈19 · ⭐ 410 · ➕) - ocp is the Open Catalyst Projects library of state-of-the-art machine.. MIT
  • exmol (🥇19 · ⭐ 240 · ➕) - Explainer for black box models that predict molecule properties. MIT
  • FitSNAP (🥈19 · ⭐ 100 · ➕) - Software for generating SNAP machine-learning interatomic.. ❗️GPL-2.0
  • FLARE (🥈18 · ⭐ 220 · ➕) - An open-source Python package for creating fast and accurate interatomic.. MIT
  • e3nn-jax (🥈18 · ⭐ 110 · ➕) - jax library for E3 Equivariant Neural Networks. Apache-2
  • MatGL (Materials Graph Library) (🥈18 · ⭐ 70 · ➕) - Graph deep learning library for materials. BSD-3
  • Scikit-Matter (🥈18 · ⭐ 58 · ➕) - BSD-3 scikit-learn
  • MALA (🥇18 · ⭐ 33 · ➕) - Materials Learning Algorithms. A framework for machine learning materials.. BSD-3
  • M3GNet (🥈17 · ⭐ 160 · ➕) - Materials graph network with 3-body interactions featuring a DFT.. BSD-3
  • XenonPy (🥈17 · ⭐ 110 · ➕) - XenonPy is a Python Software for Materials Informatics. BSD-3
  • Chemiscope (🥇17 · ⭐ 86 · ➕) - BSD-3
  • MAST-ML (🥈17 · ⭐ 82 · ➕) - MAterials Simulation Toolkit for Machine Learning (MAST-ML). MIT
  • DADApy (🥇17 · ⭐ 63 · ➕) - Distance-based Analysis of DAta-manifolds in python. Apache-2
  • Uni-Fold (🥇16 · ⭐ 260 · ➕) - An open-source platform for developing protein models beyond.. Apache-2
  • QML (🥉16 · ⭐ 180 · 💀) - QML: Quantum Machine Learning. MIT
  • ALIGNN (🥈16 · ⭐ 130 · ➕) - Atomistic Line Graph Neural Network. ❗Unlicensed
  • sGDML (🥈16 · ⭐ 110 · ➕) - sGDML - Reference implementation of the Symmetric Gradient Domain.. MIT
  • CatLearn (🥇16 · ⭐ 86 · ➕) - ❗️GPL-3.0
  • benchmarking-gnns (🥈15 · ⭐ 2.2K · 💀) - Repository for benchmarking graph neural networks. MIT
  • Uni-Mol (🥈15 · ⭐ 340 · ➕) - Official Repository for the Uni-Mol Series Methods. MIT
  • MoLeR (🥇15 · ⭐ 180 · ➕) - Implementation of MoLeR: a generative model of molecular graphs which.. MIT
  • Librascal (🥇15 · ⭐ 68 · ➕) - A scalable and versatile library to generate representations.. ❗️LGPL-2.1
  • SpheriCart (🥇15 · ⭐ 34 · 🐣) - Multi-language library for the calculation of spherical.. Apache-2
  • KLIFF (🥈15 · ⭐ 26 · ➕) - KIM-based Learning-Integrated Fitting Framework (KLIFF). ❗️LGPL-2.1
  • CCS_fit (🥈15 · ⭐ 5 · ➕) - Curvature Constrained Splines. ❗️GPL-3.0
  • n2p2 (🥈14 · ⭐ 180 · 💤) - n2p2 - A Neural Network Potential Package. ❗️GPL-3.0
  • DeepH-pack (🥇14 · ⭐ 110 · ➕) - Deep neural networks for density functional theory Hamiltonian. MIT
  • gpax (🥈14 · ⭐ 81 · ➕) - Structured Gaussian Processes and Deep Kernel Learning. MIT
  • JARVIS-Leaderboard (🥇14 · ⭐ 19 · ➕) - This project provides benchmark-performances for.. ❗Unlicensed
  • SISSO (🥈13 · ⭐ 160 · ➕) - A data-driven method combining symbolic regression and.. Apache-2
  • MACE (🥈13 · ⭐ 160 · ➕) - MACE - Fast and accurate machine learning interatomic potentials.. ❗Unlicensed
  • Automatminer (🥉13 · ⭐ 120 · 💀) - An automatic engine for predicting materials properties. ❗Unlicensed
  • PyXtalFF (🥈13 · ⭐ 68 · ➕) - Machine Learning Interatomic Potential Predictions. ❗Unlicensed
  • Ultra-Fast Force Fields (UF3) (🥈13 · ⭐ 28 · 💤) - UF3: a python library for generating ultra-fast.. Apache-2
  • Equistore (🥉13 · ⭐ 23 · ➕) - Storage format for equivariant atomistic machine learning. BSD-3
  • aviary (🥇13 · ⭐ 23 · ➕) - The Wren sits on its Roost in the Aviary. MIT
  • Polynomials4ML.jl (🥈13 · ⭐ 3 · ➕) - Polynomials for ML: fast evaluation, batching,.. MIT
  • Crystal Graph Convolutional Neural Networks (CGCNN) (🥈12 · ⭐ 470 · 💀) - Crystal graph convolutional neural networks for.. MIT
  • DMFF (🥈12 · ⭐ 97 · ➕) - DMFF (Differentiable Molecular Force Field) is a Jax-based python.. ❗️LGPL-3.0
  • SchNetPack G-SchNet (🥈12 · ⭐ 18 · ➕) - G-SchNet extension for SchNetPack. MIT
  • Compositionally-Restricted Attention-Based Network (CrabNet) (🥈12 · ⭐ 10 · ➕) - Predict materials properties using only the.. MIT
  • OpenChem (🥉11 · ⭐ 530 · 💀) - OpenChem: Deep Learning toolkit for Computational Chemistry and Drug.. MIT
  • Deep Learning for Molecules and Materials Book (🥇11 · ⭐ 500 · ➕) - ❗Unlicensed
  • ReLeaSE (🥇11 · ⭐ 300 · 💀) - Deep Reinforcement Learning for de-novo Drug Design. MIT
  • DeepLearningLifeSciences (🥇11 · ⭐ 290 · 💀) - Example code from the book Deep Learning for the Life.. MIT
  • ANI-1 (🥈11 · ⭐ 200 · 💀) - ANI-1 neural net potential with python interface (ASE). MIT
  • gptchem (🥈11 · ⭐ 150 · 🐣) - Use GPT-3 to solve chemistry problems. MIT
  • MolSkill (🥈11 · ⭐ 73 · 🐣) - Learning chemical intuition from humans in the loop... MIT
  • Neural fingerprint (nfp) (🥈11 · ⭐ 52 · 💤) - Keras layers for end-to-end learning with rdkit and.. ❗Unlicensed
  • AMPtorch (🥉11 · ⭐ 50 · ➕) - AMPtorch: Atomistic Machine Learning Package (AMP) - PyTorch. ❗️GPL-3.0
  • SIMPLE-NN (🥈11 · ⭐ 41 · 💀) - SIMPLE-NN(SNU Interatomic Machine-learning PotentiaL packagE.. ❗️GPL-3.0
  • synspace (🥈11 · ⭐ 25 · 🐣) - Synthesis generative model. MIT
  • ACE1Pack.jl (🥈11 · ⭐ 9 · ➕) - Provides convenience functionality for the usage of ACE1.jl,.. MIT
  • GDC (🥈10 · ⭐ 210 · ➕) - Graph Diffusion Convolution, as proposed in Diffusion Improves Graph.. MIT
  • Neural Force Field (🥈10 · ⭐ 170 · ➕) - Neural Network Force Field based on PyTorch. MIT
  • ASAP (🥈10 · ⭐ 100 · 💀) - ASAP is a package that can quickly analyze and visualize datasets of.. MIT
  • nlcc (🥉10 · ⭐ 41 · ➕) - Natural language computational chemistry command line.. ❗Unlicensed
  • Pacemaker (🥈10 · ⭐ 36 · ➕) - Python package for fitting ACE potentials. ❗Unlicensed
  • jarvis-tools-notebooks (🥈10 · ⭐ 36 · ➕) - A Google-Colab Notebook Collection for Materials.. ❗Unlicensed
  • flare++ (🥉10 · ⭐ 33 · 💀) - A many-body extension of the FLARE code. MIT
  • cmlkit (🥈10 · ⭐ 29 · 💀) - tools for machine learning in condensed matter physics and quantum.. MIT
  • NeuralXC (🥈10 · ⭐ 28 · 💀) - Implementation of a machine learned density functional. BSD-3
  • OpenKIM (🥈10 · ⭐ 28 · 💀) - The Open Knowledgebase of Interatomic Models (OpenKIM) aims.. ❗️LGPL-2.1
  • Finetuna (🥇10 · ⭐ 23 · ➕) - Active Learning for Machine Learning Potentials. MIT
  • iam-notebooks (🥈10 · ⭐ 16 · ➕) - Jupyter notebooks for the lectures of the Introduction to.. Apache-2
  • Rascaline (🥈10 · ⭐ 11 · ➕) - Computing representations for atomistic machine learning. BSD-3
  • NNsforMD (🥈10 · ⭐ 9 · 💤) - Neural network class for molecular dynamics to predict potential.. MIT
  • molecularGNN_smiles (🥈9 · ⭐ 240 · 💀) - The code of a graph neural network (GNN) for.. Apache-2
  • Allegro (🥉9 · ⭐ 190 · ➕) - Allegro is an open-source code for building highly scalable and.. MIT
  • SchNet (🥉9 · ⭐ 170 · 💀) - SchNet - a deep learning architecture for quantum chemistry. MIT
  • QDF for molecule (🥇9 · ⭐ 160 · 💀) - Quantum deep field: data-driven wave function, electron.. MIT
  • DeePKS-kit (🥈9 · ⭐ 92 · ➕) - a package for developing machine learning-based chemically.. ❗️LGPL-3.0
  • PiNN (🥉9 · ⭐ 89 · ➕) - A Python library for building atomic neural networks. BSD-3
  • GATGNN: Global Attention Graph Neural Network (🥈9 · ⭐ 58 · 💤) - Pytorch Repository for our work: Graph convolutional.. MIT
  • matsciml (🥈9 · ⭐ 43 · ➕) - Open MatSci ML Toolkit is a single framework for prototyping and.. MIT
  • GAP (🥉9 · ⭐ 28 · ➕) - Gaussian Approximation Potential (GAP). ❗Unlicensed
  • ACE1.jl (🥉9 · ⭐ 18 · ➕) - Atomic Cluster Expansion for Modelling Invariant Atomic.. ❗Unlicensed
  • BenchML (🥉9 · ⭐ 13 · ➕) - ML benchmarking and pipeling framework. Apache-2
  • bVAE-IM (🥈9 · ⭐ 3 · 🐣) - Implementation of Chemical Design with GPU-based Ising Machine. MIT
  • ML4pXRDs (🥈9 · 🐣) - Contains code to train neural networks based on simulated powder XRDs.. MIT
  • DimeNet (🥉8 · ⭐ 240 · ➕) - DimeNet and DimeNet++ models, as proposed in Directional.. ❗Unlicensed
  • ANI-1 Dataset (🥈8 · ⭐ 87 · 💤) - A data set of 20 million calculated off-equilibrium.. MIT
  • MoleculeNet Leaderboard (🥈8 · ⭐ 68 · 💀) - MIT
  • ACE.jl (🥉8 · ⭐ 58 · ➕) - Parameterisation of Equivariant Properties of Particle.. ❗Unlicensed
  • cG-SchNet (🥉8 · ⭐ 43 · ➕) - cG-SchNet - a conditional generative neural network for 3d molecular.. MIT
  • Sketchmap (🥉8 · ⭐ 39 · ➕) - Suite of programs to perform non-linear dimensionality.. ❗️GPL-3.0
  • SNAP (🥉8 · ⭐ 31 · 💀) - Repository for spectral neighbor analysis potential (SNAP) model.. BSD-3
  • DeeperGATGNN (🥉8 · ⭐ 30 · ➕) - Scalable graph neural networks for materials property prediction. MIT
  • So3krates (MLFF) (🥉8 · ⭐ 29 · ➕) - Build neural networks for machine learning force fields with.. MIT
  • DeepErwin (🥇8 · ⭐ 27 · ➕) - DeepErwin is a python 3.8+ package that implements and.. ❗Unlicensed
  • Atomistic Adversarial Attacks (🥉8 · ⭐ 24 · 💤) - Code for performing adversarial attacks on atomistic.. MIT
  • UVVisML (🥉8 · ⭐ 10 · ➕) - Predict optical properties of molecules with machine.. MIT
  • Equisolve (🥉8 · ⭐ 3 · ➕) - A package tasked with taking equistore objects and computing machine.. BSD-3
  • SE(3)-Transformers (🥉7 · ⭐ 380 · 💀) - code for the SE3 Transformers paper:.. ❗Unlicensed
  • RDKit Tutorials (🥈7 · ⭐ 180 · ➕) - Tutorials to learn how to work with the RDKit. ❗Unlicensed
  • GemNet (🥉7 · ⭐ 140 · ➕) - GemNet model in PyTorch, as proposed in GemNet: Universal.. ❗Unlicensed
  • G-SchNet (🥉7 · ⭐ 110 · ➕) - G-SchNet - a generative model for 3d molecular structures. MIT
  • DTNN (🥉7 · ⭐ 77 · 💀) - Deep Tensor Neural Network. MIT
  • AIMNet (🥉7 · ⭐ 75 · 💀) - Atoms In Molecules Neural Network Potential. MIT
  • PhysNet (🥉7 · ⭐ 72 · 💀) - Code for training PhysNet models. MIT
  • uncertainty_benchmarking (🥉7 · ⭐ 33 · 💀) - Various code/notebooks to benchmark different ways we.. ❗Unlicensed
  • torchchem (🥉7 · ⭐ 32 · 💀) - An experimental repo for experimenting with PyTorch models. MIT
  • ALF (🥉7 · ⭐ 15 · 🐣) - A framework for performing active learning for training.. ❗Unlicensed
  • AdsorbML (🥉7 · ⭐ 14 · ➕) - MIT
  • SA-GPR (🥉7 · ⭐ 14 · 💤) - Public repository for symmetry-adapted Gaussian Process.. ❗️LGPL-3.0
  • Libnxc (🥈7 · ⭐ 12 · 💀) - A library for using machine-learned exchange-correlation.. MPL-2.0
  • SALTED (🥈7 · ⭐ 9 · ➕) - Program for doing symmetry-adapted learning of three-dimensional.. ❗️GPL-3.0
  • CGAT (🥉7 · ⭐ 9 · ➕) - Crystal graph attention neural networks for materials prediction. MIT
  • ACEhamiltonians (🥈7 · ⭐ 5 · ➕) - Provides tools for constructing, fitting, and.. ❗Unlicensed
  • ACEfit (🥉7 · ⭐ 2 · ➕) - MIT
  • BestPractices (🥈6 · ⭐ 120 · 💀) - Things that you should (and should not) do in your Materials.. MIT
  • Equiformer (🥉6 · ⭐ 90 · 🐣) - [ICLR23 Spotlight] Equiformer: Equivariant Graph Attention.. MIT
  • ANI-1x Datasets (🥈6 · ⭐ 44 · 💀) - The ANI-1ccx and ANI-1x data sets, coupled-cluster and density.. MIT
  • Applied AI for Materials (🥈6 · ⭐ 41 · 💀) - Course materials for Applied AI for Materials Science.. ❗Unlicensed
  • COMP6 Benchmark dataset (🥈6 · ⭐ 34 · 💀) - COMP6 Benchmark dataset for ML potentials. MIT
  • DeepDFT (🥉6 · ⭐ 32 · ➕) - Official implementation of DeepDFT model. MIT
  • SIMPLE-NN v2 (🥉6 · ⭐ 19 · ➕) - ❗️GPL-3.0
  • PACE (🥉6 · ⭐ 16 · ➕) - The pair_style ACE MLP implemented in LAMMPS, aka ML-PACE. ❗Unlicensed
  • CBFV (🥈6 · ⭐ 11 · 💀) - Tool to quickly create a composition-based feature vector. ❗Unlicensed
  • testing-framework (🥉6 · ⭐ 11 · 💀) - The purpose of this repository is to aid the testing.. ❗Unlicensed
  • NICE (🥈6 · ⭐ 10 · ➕) - NICE (N-body Iteratively Contracted Equivariants) is a set of tools designed.. MIT
  • fplib (🥈6 · ⭐ 7 · 💀) - a fingerprint library. MIT
  • SOAPxx (🥈6 · ⭐ 7 · 💀) - A SOAP implementation. ❗️GPL-2.0
  • COSMO Toolbox (🥉6 · ⭐ 6 · 💤) - Assorted libraries and utilities for atomistic.. ❗Unlicensed
  • COSMO Software Cookbook (🥈6 · ⭐ 2 · 🐣) - The COSMO cookbook contains recipes for atomic-scale.. BSD-3
  • pyLODE (🥈6 · ⭐ 2 · 💤) - Pythonic implementation of LOng Distance Equivariants. Apache-2
  • Data Handling, DoE and Statistical Analysis for Material Chemists (🥈6 · 🐣) - Notebooks for workshops of DoE course, hosted by the.. ❗️GPL-3.0
  • Per-Site CGCNN (🥉6 · 🐣) - Crystal graph convolutional neural networks for predicting.. MIT
  • Per-site PAiNN (🥉6 · ➕) - Fork of PaiNN for PerovskiteOrderingGCNNs. MIT
  • GEOM (🥉5 · ⭐ 120 · 💀) - GEOM: Energy-annotated molecular conformations. ❗Unlicensed
  • JAXChem (🥉5 · ⭐ 74 · 💀) - JAXChem is a JAX-based deep learning library for complex and.. ❗Unlicensed
  • AI4Science101 (🥉5 · ⭐ 63 · 💤) - AI for Science. ❗Unlicensed
  • SchNOrb (🥉5 · ⭐ 49 · 💀) - Unifying machine learning and quantum chemistry with a deep neural.. MIT
  • hippynn (🥉5 · ⭐ 39 · ➕) - python library for atomistic machine learning. ❗Unlicensed
  • Machine Learning for Materials Hard and Soft (🥉5 · ⭐ 29 · 💤) - ESI-DCAFM-TACO-VDSP Summer School on Machine Learning.. ❗Unlicensed
  • MACE-Jax (🥉5 · ⭐ 28 · 🐣) - Equivariant machine learning interatomic potentials in JAX. ❗Unlicensed
  • milad (🥉5 · ⭐ 26 · ➕) - Moment Invariants Local Atomic Descriptor. ❗Unlicensed
  • MACE-Layer (🥉5 · ⭐ 20 · ➕) - Higher order equivariant graph neural networks for 3D point clouds. MIT
  • chargetransfernnp (🥉5 · ⭐ 20 · 💀) - Graph neural network potential with charge transfer. MIT
  • SCFNN (🥉5 · ⭐ 13 · 💀) - Self-consistent determination of long-range electrostatics.. MIT
  • rxngenerator (🥉5 · ⭐ 11 · 💤) - A generative model for molecular generation via multi-step.. MIT
  • CatGym (🥉5 · ⭐ 9 · 💀) - Surface segregation using Deep Reinforcement Learning. ❗Unlicensed
  • graphite (🥉5 · ⭐ 9 · ➕) - A repository for implementing graph network models based on.. ❗Unlicensed
  • ACEHAL (🥉5 · ⭐ 7 · 🐣) - Hyperactive Learning (HAL) Python interface for.. ❗Unlicensed
  • Alchemical learning (🥉5 · ⭐ 2 · ➕) - Code for the Modeling high-entropy transition metal.. BSD-3
  • MolSLEPA (🥉5 · ⭐ 2 · 🐣) - Interpretable Fragment-based Molecule Design with Self-learning.. MIT
  • COSMO tools (🥉5 · ⭐ 1 · 💤) - Scripts, jupyter nbs, and general helpful stuff from COSMO.. ❗Unlicensed
  • Computational Autonomy for Materials Discovery (CAMD) (🥈5 · ⭐ 1 · 🐣) - Agent-based sequential learning software for.. Apache-2
  • MAChINE (🥉5 · ⭐ 1 · 🐣) - Client-Server Web App to introduce usage of ML in materials science to.. MIT
  • linear-regression-benchmarks (🥉5 · ⭐ 1 · 💀) - Data sets used for linear regression benchmarks. MIT
  • MALADA (🥉5 · ➕) - MALA Data Acquisition: Helpful tools to build data for MALA. BSD-3
  • atombyatom (🥉5 · 🐣) - Atom-by-atom design of metal oxide catalysts for the.. ❗Unlicensed
  • ML-in-chemistry-101 (🥉4 · ⭐ 49 · 💀) - The course materials for Machine Learning in.. ❗Unlicensed
  • DeepH-E3 (🥉4 · ⭐ 20 · 🐣) - General framework for E(3)-equivariant neural network.. MIT
  • GLAMOUR (🥉4 · ⭐ 17 · ➕) - Graph Learning over Macromolecule Representations. ❗Unlicensed
  • glp (🥉4 · ⭐ 10 · 🐣) - tools for graph-based machine-learning potentials in jax. MIT
  • TensorPotential (🥉4 · ⭐ 5 · ➕) - TensorFlow based interface for ML potentials.. ❗Unlicensed
  • PANNA (🥉4 · ⭐ 5 · 💀) - A package to train and validate all-to-all connected network.. ❗Unlicensed
  • charge-density-models (🥉4 · ⭐ 2 · ➕) - Tools to build charge density models using ocpmodels. MIT
  • magnetism-prediction (🥉4 · ⭐ 1 · ➕) - DFT-aided Machine Learning Search for Magnetism in.. Apache-2
  • Wigner Kernels (🥉4 · 🐣) - Collection of programs to benchmark Wigner kernels. ❗Unlicensed
  • CSNN (🥉4 · 💤) - Primary codebase of CSNN - Concentric Spherical Neural Network for 3D.. BSD-3
  • Coarse-Graining-Auto-encoders (🥉3 · ⭐ 18 · 💀) - ❗Unlicensed
  • Graph Transport Network (🥉3 · ⭐ 14 · ➕) - Graph transport network (GTN), as proposed in.. ❗Unlicensed
  • ML-DFT (🥉3 · ⭐ 13 · 💀) - A package for density functional approximation using machine learning. MIT
  • CSPML (crystal structure prediction with machine learning-based element substitution) (🥈3 · ⭐ 11 · 💤) - Original implementation of CSPML. ❗Unlicensed
  • AGOX (🥈3 · ⭐ 10 · 💀) - AGOX is a package for global optimization of atomic system.. ❗Unlicensed
  • FieldSchNet (🥉3 · ⭐ 9 · 💀) - ❗Unlicensed
  • SPINNER (🥈3 · ⭐ 7 · 💀) - SPINNER (Structure Prediction of Inorganic crystals using.. ❗️GPL-3.0
  • 3DSC Database (🥉3 · ⭐ 5 · ➕) - Repo for the paper publishing the superconductor.. ❗Unlicensed
  • ACEatoms (🥉3 · ⭐ 2 · ➕) - Generic code for modelling atomic properties using ACE. ❗Unlicensed
  • e3psi (🥉3 · ⭐ 2 · ➕) - Equivariant machine learning library for learning from electronic.. ❗️LGPL-3.0
  • ACE Workflows (🥉3 · 🐣) - Workflow Examples for ACE Models. ❗Unlicensed
  • JAX-MD (🥇3 · ➕) - ❗Unlicensed
  • Magpie (🥉3 · ➕) - Materials Agnostic Platform for Informatics and Exploration (Magpie). MIT
  • Visual Graph Datasets (🥉3 · ➕) - Datasets for the training of graph neural networks.. ❗Unlicensed
  • MEGAN: Multi Explanation Graph Attention Student (🥉3 · ➕) - Minimal implementation of graph attention student.. ❗Unlicensed
  • MLatom (🥉3 · ➕) - ❗️Custom
  • xDeepH (🥉2 · ⭐ 15 · 🐣) - Extended DeepH (xDeepH) method for magnetic materials. MIT
  • SingleNN (🥉2 · ⭐ 5 · 💀) - An efficient package for training and executing neural-.. ❗Unlicensed
  • PiNN Lab (🥉2 · ⭐ 2 · ➕) - ❗️GPL-3.0
  • BERT-PSIE-TC (🥉2 · ⭐ 2 · 🐣) - A dataset of Curie temperatures automatically extracted from.. MIT
  • quantum-structure-ml (🥉2 · ⭐ 1 · ➕) - Multi-class classification model for predicting the.. ❗Unlicensed
  • AMP (🥉2 · ➕) - Amp is an open-source package designed to easily bring machine-learning to.. ❗Unlicensed
  • BOSS (🥉2 · ➕) - Bayesian Optimization Structure Search (BOSS). ❗Unlicensed
  • gprep (🥉2 · 💀) - Fitting DFTB repulsive potentials with GPR. ❗Unlicensed
  • MLIP-3 (🥉1 · ⭐ 8 · 🐣) - MLIP-3: Active learning on atomic environments with Moment.. ❗Unlicensed
  • gkx: Green-Kubo Method in JAX (🥉1 · ⭐ 2 · 🐣) - Green-Kubo + JAX + MLPs = Anharmonic Thermal.. MIT
  • q-pac (🥉1 · ⭐ 2 · 💀) - Kernel charge equilibration method. ❗Unlicensed
  • kdft (🥉1 · ⭐ 1 · 💀) - The Kernel Density Functional (KDF) code allows generating ML based.. ❗Unlicensed
  • MALA Tutorial (🥉1 · ⭐ 1 · 🐣) - A full MALA hands-on tutorial. ❗Unlicensed
  • SISSO++ (🥉1 · ⭐ 1 · 💀) - C++ Implementation of SISSO with python bindings. ❗Unlicensed
  • Point Edge Transformer (🥉1 · ➕) - Smooth, exact rotational symmetrization for deep.. ❗Unlicensed
  • Descriptor Embedding and Clustering for Atomisitic-environment Framework (DECAF) ( ⭐ 2 · ➕) - Provides a workflow to obtain clustering of local.. ❗Unlicensed
  • KmdPlus ( ⭐ 1 · 🐣) - This module contains a class for treating kernel mean descriptor.. ❗Unlicensed
  • interface-lammps-mlip-3 (➕) - An interface between LAMMPS and MLIP (version 3). ❗Unlicensed
  • MLDensity (➕) - Linear Jacobi-Legendre expansion of the charge density for machine.. ❗Unlicensed


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best-of-atomistic-machine-learning - v2023.12.25

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best-of-atomistic-machine-learning - v2023.12.21

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Published by Irratzo over 2 years ago