materialsvirtuallab / mamlLinks
Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
☆430Updated this week
Alternatives and similar repositories for maml
Users that are interested in maml are comparing it to the libraries listed below
Sorting:
- Graph deep learning library for materials☆432Updated this week
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆444Updated 2 weeks ago
- An open-source Python package for creating fast and accurate interatomic potentials.☆335Updated last month
- A toolkit for visualizations in materials informatics.☆276Updated 2 weeks ago
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆330Updated 2 weeks ago
- A code to generate atomic structure with symmetry☆337Updated this week
- Jupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.☆265Updated this week
- atomate2 is a library of computational materials science workflows☆244Updated this week
- Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.☆296Updated 6 months ago
- 🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.☆555Updated last week
- An automatic engine for predicting materials properties.☆164Updated last year
- libAtoms/QUIP molecular dynamics framework: https://libatoms.github.io☆370Updated this week
- The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field☆361Updated last week
- Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ https://www.youtube.com/@dr_k_choudhary☆282Updated last month
- Data mining for materials science☆549Updated this week
- Deep neural networks for density functional theory Hamiltonian.☆297Updated last year
- doped is a Python software for the generation, pre-/post-processing and analysis of defect supercell calculations, implementing the defec…☆216Updated 3 weeks ago
- atomate is a powerful software for computational materials science and contains pre-built workflows.☆260Updated last year
- Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials☆432Updated last month
- n2p2 - A Neural Network Potential Package☆239Updated 6 months ago
- A Python package for manipulating atomistic data of software in computational science☆220Updated this week
- i-PI: a universal force engine☆271Updated this week
- NequIP is a code for building E(3)-equivariant interatomic potentials☆792Updated 2 weeks ago
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.☆894Updated this week
- New API client for the Materials Project☆148Updated this week
- Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals☆541Updated 2 years ago
- A general cross-platform tool for preparing simulations of molecules and complex molecular assemblies☆303Updated last month
- Things that you should (and should not) do in your Materials Informatics research.☆193Updated last year
- Curated list of known efforts in materials informatics, i.e. in modern materials science☆467Updated last month
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆193Updated this week