Alternatives and similar repositories for CGCNN_tutorial:

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

• ruihwang / MOF-CGCNN
  We developed a novel method, MOF-CGCNN, to efficiently and accurately predict the methane the volumetric uptakes at 65 bar for MOFs. Two …
  ☆18Updated 3 years ago
• michaeldalverson / CrysTens
  ☆24Updated 7 months ago
• vxfung / MatDeepLearn_DOS
  MatDeepLearn for DOS prediction
  ☆23Updated 2 years ago
• CompRhys / roost
  Representation Learning from Stoichiometry
  ☆58Updated 2 years ago
• tobacco-mofs / tobacco_3.0
  ☆53Updated 3 years ago
• Sangwon91 / PORMAKE
  Python library for the construction of porous materials using topology and building blocks.
  ☆65Updated 3 months ago
• vxfung / DOSnet
  ☆15Updated 3 years ago
• by256 / icsg3d
  3-D Inorganic Crystal Structure Generation and Property Prediction via Representation Learning (JCIM 2020)
  ☆41Updated 2 years ago
• kaist-amsg / Composition-Conditioned-Crystal-GAN
  Composition-Conditioned Crystal GAN pytorch code
  ☆43Updated 3 years ago
• MaterSim / PyXtal_FF
  Machine Learning Interatomic Potential Predictions
  ☆89Updated last year
• bobleesj / structure-analyzer-featurizer
  An interactive Python application for generating geometric features of interatomic distances, atomic environment information, and coordin…
  ☆9Updated 2 months ago
• hellozhaoming / FCP-vasp-ase
  ASE interface for fully constant potential with VASP
  ☆31Updated 5 months ago
• SeyedMohamadMoosavi / tools-cp-porousmat
  Heat capacity predictor for porous materials
  ☆12Updated 9 months ago
• zhangylch / REANN
  ☆57Updated 3 months ago
• lalaheihaihei / catalyticLAM
  Machine-Learning-Based Interatomic Potentials for Catalysis: an Universal Catalytic Large Atomic Model
  ☆32Updated 2 months ago
• bytedance / bamboo
  BAMBOO (Bytedance AI Molecular BOOster) is an AI-driven machine learning force field designed for precise and efficient electrolyte simu…
  ☆54Updated 3 months ago
• mir-group / pair_allegro
  LAMMPS pair style for Allegro deep learning interatomic potentials with parallelization support
  ☆40Updated 5 months ago
• simonverret / materials_data_api_scripts
  scripts to load all data from ICSD, Materials Project, and OQMD
  ☆54Updated 2 years ago
• Matgenix / pysisso
  Python interface to the SISSO (Sure Independence Screening and Sparsifying Operator) method.
  ☆54Updated 11 months ago
• MDIL-SNU / G-metaD
  Metadynamics code on the G-space.
  ☆14Updated 3 years ago
• Yangxinsix / curator
  A flexible workflow for on-the-fly learning of interatomic potential models.
  ☆27Updated 11 months ago
• SMTG-Bham / ShakeNBreak
  Defect structure-searching employing chemically-guided bond distortions
  ☆89Updated 2 months ago
• mogroupumd / aimd
  ☆41Updated 6 years ago
• xiaohang007 / SLICES
  SLICES: An Invertible, Invariant, and String-based Crystal Representation [2023, Nature Communications] MatterGPT, SLICES-PLUS
  ☆99Updated last week
• RishikeshMagar / OGCNN
  Crystal graph convolutional neural networks for predicting material properties.
  ☆32Updated 2 years ago
• PV-Lab / FTCP
  FTCP code
  ☆33Updated last year
• Yangxinsix / painn-sli
  This is the source code for paper "Neural Network Potentials for Accelerated Metadynamics of Oxygen Reduction Kinetics at Au-Water Interf…
  ☆22Updated 10 months ago
• MilesZhao / PGCGM
  Source code for generating materials with 20 space groups using PGCGM
  ☆33Updated 2 years ago
• atomly-materials-research-lab / GPTFF
  GPTFF allowing anyone to directly download and run the AI model in an out-of-the-box manner
  ☆49Updated 2 weeks ago
• advancesoftcorp / lammps
  Compiled binaries and sources of LAMMPS, redistributed by AdvanceSoft Corp.
  ☆47Updated this week