Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
☆466Jul 27, 2026Updated last month
Alternatives and similar repositories for maml
Users that are interested in maml are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Benchmark Suite for Machine Learning Interatomic Potentials for Materials☆115Feb 22, 2022Updated 4 years ago
- Graph deep learning library for materials☆569Aug 25, 2026Updated last week
- Software for generating machine-learning interatomic potentials for LAMMPS☆189Oct 17, 2025Updated 10 months ago
- A python library for calculating materials properties from the PES☆150Updated this week
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆402Feb 19, 2026Updated 6 months ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals☆558Apr 27, 2023Updated 3 years ago
- A toolkit for visualizations in materials informatics.☆332Aug 23, 2026Updated last week
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆474Apr 18, 2026Updated 4 months ago
- libAtoms/QUIP molecular dynamics framework: https://libatoms.github.io☆400Aug 22, 2026Updated last week
- A code to generate atomic structure with symmetry☆385Updated this week
- Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.☆333Apr 7, 2025Updated last year
- An open-source Python package for creating fast and accurate interatomic potentials.☆361Jul 7, 2026Updated last month
- atomate2 is a library of computational materials science workflows☆343Updated this week
- Jupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.☆291Jun 1, 2026Updated 3 months ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Data mining for materials science☆614Updated this week
- ASAP is a package that can quickly analyze and visualize datasets of crystal or molecular structures.☆158Jun 27, 2024Updated 2 years ago
- Machine Learning Interatomic Potential Predictions☆93Feb 15, 2024Updated 2 years ago
- Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support f…☆1,947Updated this week
- doped is a Python software for the generation, pre-/post-processing and analysis of defect supercell calculations, implementing the defec…☆277Updated this week
- atomate is a powerful software for computational materials science and contains pre-built workflows.☆263Jul 18, 2024Updated 2 years ago
- NequIP is a code for building E(3)-equivariant interatomic potentials☆958Updated this week
- An automatic engine for predicting materials properties.☆174Nov 12, 2023Updated 2 years ago
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆270Jul 22, 2026Updated last month
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- quacc is a flexible platform for computational materials science and quantum chemistry that is built for the big data era.☆284Updated this week
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.☆1,336Updated this week
- Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ https://www.youtube.com/@dr_k_choudhary☆330Aug 25, 2025Updated last year
- Atomic interaction potentials based on artificial neural networks☆128Apr 16, 2026Updated 4 months ago
- LAMMPS interface for phonon calculations using phonopy☆96Nov 5, 2025Updated 9 months ago
- Crystal graph convolutional neural networks for predicting material properties.☆892Sep 6, 2021Updated 4 years ago
- Materials science with Python at the atomic-scale☆240Aug 5, 2026Updated 3 weeks ago
- A Python package for estimating diffusion properties from molecular dynamics simulations.☆88Aug 10, 2026Updated 3 weeks ago
- n2p2 - A Neural Network Potential Package☆245Mar 17, 2025Updated last year
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Crystal Toolkit is a framework for building web apps for materials science and is currently powering the new Materials Project website.☆203Updated this week
- A foundational potential energy dataset for materials☆59Aug 4, 2026Updated 3 weeks ago
- Curated list of known efforts in materials informatics, i.e. in modern materials science☆529Mar 24, 2026Updated 5 months ago
- scalable molecular simulation☆143Apr 28, 2026Updated 4 months ago
- pyiron - an integrated development environment (IDE) for computational materials science.☆462Oct 13, 2025Updated 10 months ago
- An evaluation framework for machine learning models simulating high-throughput materials discovery.☆249Updated this week
- SchNetPack - Deep Neural Networks for Atomistic Systems☆937Aug 25, 2026Updated last week