Open-Catalyst-Project / Open-Catalyst-DatasetLinks
Workflow for creating and analyzing the Open Catalyst Dataset
☆122Updated 11 months ago
Alternatives and similar repositories for Open-Catalyst-Dataset
Users that are interested in Open-Catalyst-Dataset are comparing it to the libraries listed below
Sorting:
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆82Updated 3 years ago
- Unsupervised learning of atomic scale dynamics from molecular dynamics.☆85Updated 4 years ago
- The QMOF Database: A database of quantum-mechanical properties for metal-organic frameworks.☆158Updated 2 months ago
- Matbench: Benchmarks for materials science property prediction☆180Updated last year
- sGDML - Reference implementation of the Symmetric Gradient Domain Machine Learning model☆163Updated 7 months ago
- MatDeepLearn, package for graph neural networks in materials chemistry☆198Updated 2 years ago
- FTCP code☆36Updated 2 years ago
- ASAP is a package that can quickly analyze and visualize datasets of crystal or molecular structures.☆152Updated last year
- AMPtorch: Atomistic Machine Learning Package (AMP) - PyTorch☆61Updated 2 years ago
- Composition-Conditioned Crystal GAN pytorch code☆43Updated 3 years ago
- A system for rapid identification and analysis of metal-organic frameworks☆68Updated last month
- [npj Comp. Mat.] Higher-order equivariant neural networks for charge density prediction in materials☆70Updated 10 months ago
- Official implementation of DeepDFT model☆86Updated 2 years ago
- Representation Learning from Stoichiometry☆60Updated 3 years ago
- train and use graph-based ML models of potential energy surfaces☆118Updated last month
- A large scale benchmark of materials design methods: https://www.nature.com/articles/s41524-024-01259-w☆72Updated 2 months ago
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆210Updated 2 weeks ago
- A repository for implementing graph network models based on atomic structures.☆102Updated last year
- Corresponding dataset and tools for the AdsorbML manuscript.☆42Updated 11 months ago
- The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for organic molecules.☆67Updated 3 years ago
- Generate and predict molecular electron densities with Euclidean Neural Networks☆49Updated 2 years ago
- LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials☆59Updated 4 months ago
- ☆34Updated last year
- An evaluation framework for machine learning models simulating high-throughput materials discovery.☆206Updated this week
- 3-D Inorganic Crystal Structure Generation and Property Prediction via Representation Learning (JCIM 2020)☆43Updated 2 years ago
- NeurIPS 2018 MLMM Workshop: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Predicti…☆68Updated last year
- ☆29Updated 3 years ago
- Predict materials properties using only the composition information!☆119Updated 2 years ago
- Learning to Discover Crystallographic Structures with Generative Adversarial Networks☆39Updated 6 years ago
- A framework for performing active learning for training machine-learned interatomic potentials.☆39Updated 2 months ago