microsoft / mattersimLinks
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
☆471Updated 3 months ago
Alternatives and similar repositories for mattersim
Users that are interested in mattersim are comparing it to the libraries listed below
Sorting:
- ORB forcefield models from Orbital Materials☆503Updated last week
- Torch-native, batchable, atomistic simulations.☆336Updated this week
- Graph deep learning library for materials☆448Updated this week
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆335Updated this week
- Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials☆436Updated last month
- An evaluation framework for machine learning models simulating high-throughput materials discovery.☆197Updated this week
- 🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.☆565Updated last week
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.☆910Updated last week
- Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.☆299Updated 6 months ago
- ☆241Updated 3 weeks ago
- Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ https://www.youtube.com/@dr_k_choudhary☆285Updated 2 months ago
- A toolkit for visualizations in materials informatics.☆277Updated this week
- Foundation Model for Materials - FM4M☆262Updated last month
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆197Updated last week
- NequIP is a code for building E(3)-equivariant interatomic potentials☆808Updated 2 weeks ago
- MACE foundation models (MP, OMAT, Matpes)☆153Updated last month
- atomate2 is a library of computational materials science workflows☆248Updated this week
- Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.☆431Updated 3 weeks ago
- An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]☆334Updated last year
- Deep neural networks for density functional theory Hamiltonian.☆299Updated last year
- Open MatSci ML Toolkit is a framework for prototyping and scaling out deep learning models for materials discovery supporting widely used…☆181Updated 7 months ago
- The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field☆363Updated last week
- An open-source Python package for creating fast and accurate interatomic potentials.☆338Updated last month
- Matbench: Benchmarks for materials science property prediction☆170Updated last year
- New API client for the Materials Project☆149Updated this week
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆447Updated last month
- A plugin to use Nvidia GPU in PySCF package☆224Updated last week
- This add-on to pymatgen provides tools for analyzing diffusion in materials.☆129Updated 3 weeks ago
- doped is a Python software for the generation, pre-/post-processing and analysis of defect supercell calculations, implementing the defec…☆219Updated last week
- quacc is a flexible platform for computational materials science and quantum chemistry that is built for the big data era.☆227Updated last week