Alternatives and similar repositories for MEGNet_PyTorch:

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

• jiaor17 / DiffCSP-PP
  [ICLR 2024] The implementation for the paper "Space Group Constrained Crystal Generation"
  ☆39Updated 4 months ago
• ixsluo / cond-cdvae
  An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]
  ☆19Updated 6 months ago
• kaist-amsg / Composition-Conditioned-Crystal-GAN
  Composition-Conditioned Crystal GAN pytorch code
  ☆43Updated 3 years ago
• RishikeshMagar / Crystal-Twins
  ☆19Updated last year
• trachote / dp-cdvae
  Diffusion Probabilistic CDVAE
  ☆23Updated last year
• EmperorJia / EquiCSP
  Equivariant Diffusion for Crystal Structure Prediction (ICML 2024)
  ☆20Updated 8 months ago
• PV-Lab / FTCP
  FTCP code
  ☆34Updated last year
• lzhelin / CrystalDiffusion
  ☆10Updated 3 months ago
• NU-CUCIS / ALIGNNTL
  ☆10Updated last year
• sparks-baird / matbench-genmetrics
  Generative materials benchmarking metrics, inspired by guacamol and CDVAE.
  ☆36Updated 10 months ago
• michaeldalverson / CrysTens
  ☆24Updated 8 months ago
• MilesZhao / PGCGM
  Source code for generating materials with 20 space groups using PGCGM
  ☆32Updated 2 years ago
• gomes-lab / Mat2Spec
  ☆28Updated 3 years ago
• dhw059 / DenseGNN
  DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules
  ☆20Updated 3 months ago
• Tinystormjojo / geo-CGNN
  ☆33Updated 9 months ago
• usccolumbia / deeperGATGNN
  Scalable graph neural networks for materials property prediction
  ☆58Updated last year
• CompRhys / roost
  Representation Learning from Stoichiometry
  ☆59Updated 2 years ago
• kdmsit / Awesome-Crystal-GNNs
  This repository contains a collection of resources and papers on GNN Models on Crystal Solid State Materials
  ☆92Updated 2 months ago
• usnistgov / jarvis_leaderboard
  A large scale benchmark of materials design methods: https://www.nature.com/articles/s41524-024-01259-w
  ☆68Updated last month
• RishikeshMagar / OGCNN
  Crystal graph convolutional neural networks for predicting material properties.
  ☆32Updated 2 years ago
• matbench-submission-coGN / CrystalGNNs
  ☆10Updated last year
• JoshRackers / equivariant_electron_density
  Generate and predict molecular electron densities with Euclidean Neural Networks
  ☆47Updated last year
• Minoru938 / CSPML
  Original implementation of CSPML
  ☆24Updated 4 months ago
• peterbjorgensen / DeepDFT
  Official implementation of DeepDFT model
  ☆75Updated 2 years ago
• mir-group / pair_nequip_allegro
  LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials
  ☆40Updated this week
• OUnke / SpookyNet
  Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"
  ☆72Updated 2 years ago
• anthony-wang / CrabNet
  Predict materials properties using only the composition information!
  ☆100Updated 2 years ago
• bytedance / bamboo
  BAMBOO (Bytedance AI Molecular BOOster) is an AI-driven machine learning force field designed for precise and efficient electrolyte simu…
  ☆75Updated 3 months ago
• Diego-2504 / CGCNN_tutorial
  Crystal Graph Convolutional Neural Networks tutorial
  ☆24Updated 2 years ago
• by256 / icsg3d
  3-D Inorganic Crystal Structure Generation and Property Prediction via Representation Learning (JCIM 2020)
  ☆41Updated 2 years ago