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. 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
• tmQM_wB97MV Dataset (🥉2 · ⭐ 5 · ➕) - Code for Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV.. 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