Alternatives and similar repositories for applied-ai-for-materials

Users that are interested in applied-ai-for-materials are comparing it to the libraries listed below

• TRI-AMDD / CAMD
  Agent-based sequential learning software for materials discovery
  ☆62Updated last year
• SergeiVKalinin / MSE_Fall2024
  ☆62Updated 6 months ago
• MLMI2-CSSI / foundry
  Simplifying the discovery and usage of machine-learning ready datasets in materials science and chemistry
  ☆80Updated 2 weeks ago
• sparks-baird / xtal2png
  Encode/decode a crystal structure to/from a grayscale PNG image for direct use with image-based machine learning models such as Palette.
  ☆37Updated last year
• pyscal / pyscal
  Python library written in C++ for calculation of local atomic structural environment
  ☆61Updated 9 months ago
• lanl / ALF
  A framework for performing active learning for training machine-learned interatomic potentials.
  ☆35Updated last month
• openkim / kliff
  KIM-based Learning-Integrated Fitting Framework for interatomic potentials.
  ☆36Updated 2 weeks ago
• jkitchin / dft-book-espresso
  New version of dft-book for Quantum Espresso
  ☆45Updated 5 years ago
• sparks-baird / mat_discover
  A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
  ☆44Updated 9 months ago
• bjmorgan / kinisi
  A Python package for estimating diffusion properties from molecular dynamics simulations.
  ☆68Updated last month
• MaterSim / PyXtal_FF
  Machine Learning Interatomic Potential Predictions
  ☆90Updated last year
• angeloziletti / ai4materials
  Deep learning for crystal-structure recognition and analysis of atomic structures
  ☆41Updated last year
• learningmatter-mit / surface-sampling
  MCMC-based algorithm for sampling surface reconstructions
  ☆30Updated last month
• MihailBogojeski / ml-dft
  A package for density functional approximation using machine learning.
  ☆26Updated 4 years ago
• autoatml / autoplex
  Code for automated fitting of machine learned interatomic potentials.
  ☆77Updated this week
• CSIprinceton / workshop-july-2020
  Molecular Simulation with Machine Learning - On-line workshop, July 13-14, 2020
  ☆22Updated 4 years ago
• cagrikymk / JAX-ReaxFF
  JAX-ReaxFF: A Gradient Based Framework for Extremely Fast Optimization of Reactive Force Fields
  ☆65Updated 8 months ago
• materialsvirtuallab / nano281
  Data Science for Materials Science
  ☆63Updated last week
• lanl / hippynn
  python library for atomistic machine learning
  ☆78Updated 3 weeks ago
• hsulab / GDPy
  Generating Deep Potential with Python
  ☆67Updated this week
• BingqingCheng / ML-in-chemistry-101
  The course materials for "Machine Learning in Chemistry 101"
  ☆77Updated 4 years ago
• libAtoms / GAP
  ☆41Updated last month
• jan-janssen / LangSim
  Application of Large Language Models (LLM) for computational materials science - visit jan-janssen.com/LangSim
  ☆63Updated 7 months ago
• learningmatter-mit / Atomistic-Adversarial-Attacks
  Code for performing adversarial attacks on atomistic systems using NN potentials
  ☆38Updated 2 years ago
• hackingmaterials / robocrystallographer
  Automatic generation of crystal structure descriptions.
  ☆118Updated this week
• ceriottm / iam-notebooks
  Jupyter notebooks for the lectures of the Introduction to Atomistic Modeling
  ☆28Updated last month
• lammpstutorials / lammpstutorials-inputs
  LAMMPS input from lammpstutorials.github.io
  ☆42Updated last month
• mir-group / flare_pp
  A many-body extension of the FLARE code.
  ☆36Updated 3 years ago
• dskoda / quests
  Quick Uncertainty and Entropy via STructural Similarity
  ☆44Updated 3 weeks ago
• pyiron / pyiron_atomistics
  pyiron_atomistics - an integrated development environment (IDE) for atomistic simulation in computational materials science.
  ☆45Updated last week