Alternatives and similar repositories for roost:

Users that are interested in roost are comparing it to the libraries listed below

• by256 / icsg3d
  3-D Inorganic Crystal Structure Generation and Property Prediction via Representation Learning (JCIM 2020)
  ☆40Updated 2 years ago
• kaist-amsg / imatgen
  image-based generative model for inverse design of solid state materials
  ☆39Updated 3 years ago
• Tinystormjojo / geo-CGNN
  ☆33Updated 7 months ago
• MaterSim / PyXtal_FF
  Machine Learning Interatomic Potential Predictions
  ☆89Updated last year
• atomisticnet / tools-and-data
  A collection of tools and databases for atomistic machine learning
  ☆47Updated 3 years ago
• gomes-lab / Mat2Spec
  ☆28Updated 2 years ago
• CJBartel / TestStabilityML
  ☆27Updated last year
• RishikeshMagar / OGCNN
  Crystal graph convolutional neural networks for predicting material properties.
  ☆31Updated 2 years ago
• txie-93 / gdynet
  Unsupervised learning of atomic scale dynamics from molecular dynamics.
  ☆80Updated 3 years ago
• hyllios / CGAT
  Crystal graph attention neural networks for materials prediction
  ☆27Updated last year
• Sangwon91 / PORMAKE
  Python library for the construction of porous materials using topology and building blocks.
  ☆62Updated last month
• PV-Lab / FTCP
  FTCP code
  ☆33Updated last year
• kaist-amsg / Composition-Conditioned-Crystal-GAN
  Composition-Conditioned Crystal GAN pytorch code
  ☆43Updated 2 years ago
• vxfung / MatDeepLearn_DOS
  MatDeepLearn for DOS prediction
  ☆22Updated 2 years ago
• hoffmannjordan / Encoding-Decoding-3D-Crystals
  "Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures", Jordan Hoffmann, Louis Maestrati, Yoshihide Sawada, Jian Tang, Je…
  ☆35Updated 5 years ago
• lrcfmd / ipcsp
  Integer Programming encoding for Crystal Structure Prediction with classic and quantum computing bindings
  ☆47Updated last year
• MilesZhao / CubicGAN
  This is the source code of CubicGAN generating cubic crystal structures using improved WGAN.
  ☆10Updated 2 years ago
• lrcfmd / ElMD
  The Element Movers Distance for chemical composition similarity
  ☆33Updated 3 months ago
• OUnke / SpookyNet
  Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"
  ☆69Updated 2 years ago
• Minoru938 / CSPML
  Original implementation of CSPML
  ☆23Updated last month
• Tsotsalas-Group / MOF_Literature_Extraction
  ☆29Updated 3 years ago
• ulissigroup / finetuna
  Active Learning for Machine Learning Potentials
  ☆49Updated 9 months ago
• anthony-wang / CrabNet
  Predict materials properties using only the composition information!
  ☆98Updated last year
• asmanouira / CrystalGAN
  Learning to Discover Crystallographic Structures with Generative Adversarial Networks
  ☆37Updated 5 years ago
• MDIL-SNU / SIMPLE-NN
  SIMPLE-NN(SNU Interatomic Machine-learning PotentiaL packagE – version Neural Network)
  ☆46Updated 3 years ago
• CompRhys / aviary
  The Wren sits on its Roost in the Aviary.
  ☆51Updated 2 weeks ago
• usnistgov / jarvis_leaderboard
  A large scale benchmark of materials design methods: https://www.nature.com/articles/s41524-024-01259-w
  ☆63Updated last month
• simonverret / materials_data_api_scripts
  scripts to load all data from ICSD, Materials Project, and OQMD
  ☆53Updated 2 years ago
• snurr-group / mofid
  A system for rapid identification and analysis of metal-organic frameworks
  ☆48Updated 2 months ago
• sparks-baird / matbench-genmetrics
  Generative materials benchmarking metrics, inspired by guacamol and CDVAE.
  ☆35Updated 8 months ago