kaist-amsg / imatgenLinks
image-based generative model for inverse design of solid state materials
☆41Updated 3 years ago
Alternatives and similar repositories for imatgen
Users that are interested in imatgen are comparing it to the libraries listed below
Sorting:
- ☆34Updated 3 years ago
- Composition-Conditioned Crystal GAN pytorch code☆43Updated 3 years ago
- Learning to Discover Crystallographic Structures with Generative Adversarial Networks☆39Updated 6 years ago
- Representation Learning from Stoichiometry☆59Updated 2 years ago
- 3-D Inorganic Crystal Structure Generation and Property Prediction via Representation Learning (JCIM 2020)☆41Updated 2 years ago
- Crystal Edge Graph Attention Neural Network☆24Updated last year
- ☆34Updated 2 months ago
- Original implementation of CSPML☆28Updated 11 months ago
- ☆29Updated 3 years ago
- ☆16Updated 3 years ago
- A system for rapid identification and analysis of metal-organic frameworks☆63Updated last year
- Graph neural network potential with charge transfer☆36Updated 3 years ago
- Unsupervised learning of atomic scale dynamics from molecular dynamics.☆83Updated 3 years ago
- ☆26Updated last year
- This is the source code of CubicGAN generating cubic crystal structures using improved WGAN.☆10Updated 3 years ago
- A collection of tools and databases for atomistic machine learning☆48Updated 4 years ago
- ☆30Updated 4 years ago
- "Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures", Jordan Hoffmann, Louis Maestrati, Yoshihide Sawada, Jian Tang, Je…☆35Updated 6 years ago
- ☆34Updated last year
- GemNet model in TensorFlow, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)☆27Updated 2 years ago
- Materials Transformers☆25Updated 2 years ago
- FTCP code☆35Updated 2 years ago
- Crystal graph convolutional neural networks for predicting material properties.☆34Updated 3 years ago
- ☆23Updated last year
- Source code for generating materials with 20 space groups using PGCGM☆34Updated 2 years ago
- ☆26Updated 2 years ago
- Encode/decode a crystal structure to/from a grayscale PNG image for direct use with image-based machine learning models such as Palette.☆37Updated 2 years ago
- data and code to reduplicate paper: Topological representations of crystalline compounds for the machine-learning prediction of materials…☆22Updated 4 years ago
- Scalable graph neural networks for materials property prediction☆63Updated last year
- Universal Transfer Learning in Porous Materials, including MOFs.☆114Updated last year