txie-93 / cgcnn
Crystal graph convolutional neural networks for predicting material properties.
☆684Updated 3 years ago
Alternatives and similar repositories for cgcnn:
Users that are interested in cgcnn are comparing it to the libraries listed below
- Graph deep learning library for materials☆303Updated this week
- Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals☆512Updated last year
- An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]☆257Updated 5 months ago
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.☆594Updated this week
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆267Updated this week
- SchNetPack - Deep Neural Networks for Atomistic Systems☆814Updated this week
- 🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.☆430Updated this week
- Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ&hl=en https://www.youtube.com/watch?v=WYePj…☆247Updated this week
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆406Updated last month
- SchNet - a deep learning architecture for quantum chemistry☆237Updated 6 years ago
- NequIP is a code for building E(3)-equivariant interatomic potentials☆672Updated 2 weeks ago
- Deep neural networks for density functional theory Hamiltonian.☆254Updated 3 months ago
- A data-driven method combining symbolic regression and compressed sensing for accurate & interpretable models.☆262Updated 3 months ago
- Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.☆383Updated last week
- FAIR Chemistry's library of machine learning methods for chemistry☆954Updated this week
- Data mining for materials science☆495Updated this week
- MatDeepLearn, package for graph neural networks in materials chemistry☆179Updated last year
- Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.☆261Updated last week
- Public repo for Materials API documentation☆140Updated 2 years ago
- An open-source Python package for creating fast and accurate interatomic potentials.☆307Updated last week
- DimeNet and DimeNet++ models, as proposed in "Directional Message Passing for Molecular Graphs" (ICLR 2020) and "Fast and Uncertainty-Awa…☆308Updated last year
- Deep Learning the Chemistry of Materials From Only Elemental Composition for Enhancing Materials Property Prediction☆92Updated last year
- Workflow for creating and analyzing the Open Catalyst Dataset☆99Updated 7 months ago
- The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field☆322Updated this week
- An automatic engine for predicting materials properties.☆142Updated last year
- Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials☆368Updated last month
- A repo of examples for the matminer (https://github.com/hackingmaterials/matminer) code☆105Updated 3 years ago
- Jupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.☆237Updated 6 months ago
- A code to generate atomic structure with symmetry☆287Updated this week
- n2p2 - A Neural Network Potential Package☆227Updated last month