kdmsit / crysgnn
CrysGNN : Distilling pre-trained knowledge to enhance property prediction for crystalline materials. (AAAI-2023)
☆27Updated 2 months ago
Alternatives and similar repositories for crysgnn:
Users that are interested in crysgnn are comparing it to the libraries listed below
- Scalable graph neural networks for materials property prediction☆56Updated last year
- A repository for implementing graph network models based on atomic structures.☆75Updated 7 months ago
- Composition-Conditioned Crystal GAN pytorch code☆43Updated 3 years ago
- Official code for Periodic Graph Transformers for Crystal Material Property Prediction (NeurIPS 2022)☆91Updated last year
- Universal Transfer Learning in Porous Materials, including MOFs.☆94Updated 9 months ago
- Source code for generating materials with 20 space groups using PGCGM☆33Updated 2 years ago
- Transformer model for structure-agnostic metal-organic frameworks (MOF) property prediction☆49Updated last year
- This repository contains a collection of resources and papers on GNN Models on Crystal Solid State Materials☆90Updated last month
- FTCP code☆33Updated last year
- Zeolite GAN☆21Updated 4 years ago
- ☆26Updated 4 months ago
- ☆18Updated last year
- ChemNLP: A Natural Language Processing based Library for Materials Chemistry Text Data☆74Updated 7 months ago
- Materials Transformers☆25Updated 2 years ago
- Official implementation of DeepDFT model☆73Updated 2 years ago
- G-SchNet extension for SchNetPack☆57Updated 4 months ago
- A large scale benchmark of materials design methods: https://www.nature.com/articles/s41524-024-01259-w☆65Updated 2 weeks ago
- Implementation of "TransPolymer: a Transformer-based language model for polymer property predictions" in PyTorch☆68Updated last year
- ☆17Updated 7 months ago
- 3-D Inorganic Crystal Structure Generation and Property Prediction via Representation Learning (JCIM 2020)☆41Updated 2 years ago
- DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules☆18Updated 2 months ago
- ☆10Updated last year
- ☆33Updated 8 months ago
- ☆24Updated 7 months ago
- Code for “From Molecules to Materials Pre-training Large Generalizable Models for Atomic Property Prediction”.☆55Updated 5 months ago
- image-based generative model for inverse design of solid state materials☆39Updated 3 years ago
- A Large Language Model of the CIF format for Crystal Structure Generation☆99Updated 2 months ago
- GemNet model in TensorFlow, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)☆25Updated last year
- Crystal Edge Graph Attention Neural Network☆19Updated 9 months ago
- ☆28Updated 2 years ago