Alternatives and similar repositories for ZeoGAN

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

• kaist-amsg / Composition-Conditioned-Crystal-GAN
  Composition-Conditioned Crystal GAN pytorch code
  ☆43Updated 3 years ago
• PV-Lab / FTCP
  FTCP code
  ☆35Updated 2 years ago
• ixsluo / cond-cdvae
  An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]
  ☆25Updated last year
• hspark1212 / MOFTransformer
  Universal Transfer Learning in Porous Materials, including MOFs.
  ☆114Updated last year
• 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 …
  ☆21Updated 4 years ago
• cyye001 / Con-CDVAE
  This is a conditionally generative model for crystal structures based on a modified version of CDVAE.
  ☆37Updated last month
• sbanik2 / CEGANN
  Crystal Edge Graph Attention Neural Network
  ☆24Updated last year
• michaeldalverson / CrysTens
  ☆26Updated last year
• by256 / icsg3d
  3-D Inorganic Crystal Structure Generation and Property Prediction via Representation Learning (JCIM 2020)
  ☆41Updated 2 years ago
• MilesZhao / PGCGM
  Source code for generating materials with 20 space groups using PGCGM
  ☆34Updated 2 years ago
• xiaohang007 / SLICES
  SLICES: An Invertible, Invariant, and String-based Crystal Representation [2023, Nature Communications] MatterGPT, SLICES-PLUS
  ☆127Updated last month
• Sangwon91 / PORMAKE
  Python library for the construction of porous materials using topology and building blocks.
  ☆79Updated 6 months ago
• lantunes / CrystaLLM
  A Large Language Model of the CIF format for Crystal Structure Generation
  ☆141Updated 2 months ago
• kaist-amsg / imatgen
  image-based generative model for inverse design of solid state materials
  ☆41Updated 3 years ago
• LLNL / graphite
  A repository for implementing graph network models based on atomic structures.
  ☆96Updated last year
• jiaor17 / DiffCSP-PP
  [ICLR 2024] The implementation for the paper "Space Group Constrained Crystal Generation"
  ☆53Updated 2 weeks ago
• dhw059 / DenseGNN
  DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules
  ☆27Updated 11 months ago
• hspark1212 / chemeleon
  A text-guided diffusion model for crystal structure generation
  ☆70Updated 6 months ago
• tobacco-mofs / tobacco_3.0
  ☆65Updated 4 years ago
• zcao0420 / MOFormer
  Transformer model for structure-agnostic metal-organic frameworks (MOF) property prediction
  ☆59Updated 2 years ago
• usccolumbia / deeperGATGNN
  Scalable graph neural networks for materials property prediction
  ☆63Updated last year
• WanyuGroup / AI-for-Crystal-Materials
  AI for crystal materials
  ☆96Updated this week
• parkjunkil / ZeoDiff
  ☆20Updated 2 weeks ago
• Matgen-project / MOFNet
  Deep learning model for predicting adsorption isotherms of MOFs
  ☆15Updated 3 years ago
• OUnke / SpookyNet
  Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"
  ☆80Updated 3 years ago
• peterbjorgensen / DeepDFT
  Official implementation of DeepDFT model
  ☆85Updated 2 years ago
• snurr-group / mofid
  A system for rapid identification and analysis of metal-organic frameworks
  ☆63Updated this week
• dralgroup / mlatom
  AI-enhanced computational chemistry
  ☆122Updated 3 weeks ago
• bytedance / bamboo
  BAMBOO (Bytedance AI Molecular BOOster) is an AI-driven machine learning force field designed for precise and efficient electrolyte simu…
  ☆128Updated 3 weeks ago
• Shen-Group / E2GNN
  ☆23Updated last year