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☆575Updated this week
- Software for generating machine-learning interatomic potentials for LAMMPS☆190Oct 17, 2025Updated 11 months ago
- A python library for calculating materials properties from the PES☆152Sep 9, 2026Updated 2 weeks ago
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆412Sep 15, 2026Updated last week
- Open source password manager - Proton Pass • AdSecurely store, share, and autofill your credentials with Proton Pass, the end-to-end encrypted password manager trusted by millions.
- 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.☆335Sep 10, 2026Updated last week
- DScribe is a python package for creating machine learning descriptors for atomistic systems.☆475Apr 18, 2026Updated 5 months ago
- libAtoms/QUIP molecular dynamics framework: https://libatoms.github.io☆403Aug 22, 2026Updated last month
- A code to generate atomic structure with symmetry☆391Sep 9, 2026Updated 2 weeks ago
- Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.☆332Apr 7, 2025Updated last year
- An open-source Python package for creating fast and accurate interatomic potentials.☆362Updated this week
- atomate2 is a library of computational materials science workflows☆348Updated this week
- Jupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.☆291Jun 1, 2026Updated 3 months ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- Data mining for materials science☆616Updated this week
- ASAP is a package that can quickly analyze and visualize datasets of crystal or molecular structures.☆159Jun 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…☆1,978Updated this week
- doped is a Python software for the generation, pre-/post-processing and analysis of defect supercell calculations, implementing the defec…☆280Updated this week
- atomate is a powerful software for computational materials science and contains pre-built workflows.☆265Jul 18, 2024Updated 2 years ago
- NequIP is a code for building E(3)-equivariant interatomic potentials☆966Updated this week
- An automatic engine for predicting materials properties.☆176Nov 12, 2023Updated 2 years ago
- SevenNet - a graph neural network interatomic potential package supporting efficient multi-GPU parallel molecular dynamics simulations.☆273Jul 22, 2026Updated 2 months ago
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.☆1,359Updated this week
- quacc is a flexible platform for computational materials science and quantum chemistry that is built for the big data era.☆293Updated this week
- Atomistic Line Graph Neural Network https://scholar.google.com/citations?user=9Q-tNnwAAAAJ https://www.youtube.com/@dr_k_choudhary☆332Aug 25, 2025Updated last year
- Atomic interaction potentials based on artificial neural networks☆128Updated this week
- LAMMPS interface for phonon calculations using phonopy☆96Nov 5, 2025Updated 10 months ago
- Crystal graph convolutional neural networks for predicting material properties.☆892Sep 6, 2021Updated 5 years ago
- Materials science with Python at the atomic-scale☆246Updated this week
- A Python package for estimating diffusion properties from molecular dynamics simulations.☆88Sep 7, 2026Updated 2 weeks ago
- n2p2 - A Neural Network Potential Package☆244Mar 17, 2025Updated last year
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- Crystal Toolkit is a framework for building web apps for materials science and is currently powering the new Materials Project website.☆204Aug 28, 2026Updated 3 weeks ago
- A foundational potential energy dataset for materials☆60Aug 4, 2026Updated last month
- Curated list of known efforts in materials informatics, i.e. in modern materials science☆531Mar 24, 2026Updated 5 months ago
- scalable molecular simulation☆143Apr 28, 2026Updated 4 months ago
- pyiron - an integrated development environment (IDE) for computational materials science.☆464Oct 13, 2025Updated 11 months ago
- SchNetPack - Deep Neural Networks for Atomistic Systems☆940Updated this week
- An evaluation framework for machine learning models simulating high-throughput materials discovery.☆253Updated this week