materialsvirtuallab / mamlLinks
Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
☆413Updated 3 weeks ago
Alternatives and similar repositories for maml
Users that are interested in maml are comparing it to the libraries listed below
Sorting:
- An open-source Python package for creating fast and accurate interatomic potentials.☆325Updated this week
- Graph deep learning library for materials☆351Updated this week
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆306Updated last month
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆434Updated 5 months ago
- A code to generate atomic structure with symmetry☆315Updated last week
- Jupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.☆246Updated 3 weeks ago
- atomate2 is a library of computational materials science workflows☆221Updated this week
- An automatic engine for predicting materials properties.☆154Updated last year
- n2p2 - A Neural Network Potential Package☆236Updated 2 months ago
- Matbench: Benchmarks for materials science property prediction☆156Updated 9 months ago
- An evaluation framework for machine learning models simulating high-throughput materials discovery.☆157Updated last week
- doped is a Python software for the generation, pre-/post-processing and analysis of defect supercell calculations, implementing the defec…☆188Updated this week
- libAtoms/QUIP molecular dynamics framework: https://libatoms.github.io☆362Updated 3 weeks ago
- A toolkit for visualizations in materials informatics.☆227Updated last week
- Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.☆284Updated last month
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.☆730Updated this week
- A Python package for manipulating atomistic data of software in computational science☆211Updated this week
- Software for generating machine-learning interatomic potentials for LAMMPS☆167Updated last week
- atomate is a powerful software for computational materials science and contains pre-built workflows.☆254Updated 10 months ago
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆179Updated 2 weeks ago
- Deep neural networks for density functional theory Hamiltonian.☆279Updated 7 months ago
- 🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.☆498Updated this week
- Things that you should (and should not) do in your Materials Informatics research.☆186Updated last year
- Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ https://www.youtube.com/@dr_k_choudhary☆270Updated last month
- Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials☆399Updated last week
- Heavyweight plotting tools for ab initio calculations☆224Updated 3 weeks ago
- i-PI: a universal force engine☆258Updated this week
- Curated list of known efforts in materials informatics, i.e. in modern materials science☆442Updated 3 weeks ago
- The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field☆339Updated last week
- A general cross-platform tool for preparing simulations of molecules and complex molecular assemblies☆287Updated 2 months ago