Pinned Repositories
Awesome-Diffusion-Models-for-Science
cdvae
An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]
cgcnn
Crystal graph convolutional neural networks for predicting material properties.
CGCNN_Paddle
Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties implemented based on the Paddle framework
CSPML
Original implementation of CSPML
deep_md_test
deepmd-kit
A deep learning package for many-body potential energy representation and molecular dynamics
dielectrics
Pushing the Pareto front of band gap and permittivity with ML-guided dielectric materials discovery incl. experimental synthesis and characterization.
DiffCSP
Paddle_DeepMD-kit
leeleolay's Repositories
leeleolay/Paddle_DeepMD-kit
leeleolay/Awesome-Diffusion-Models-for-Science
leeleolay/cdvae
An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]
leeleolay/CGCNN_Paddle
Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties implemented based on the Paddle framework
leeleolay/CSPML
Original implementation of CSPML
leeleolay/deepmd-kit
A deep learning package for many-body potential energy representation and molecular dynamics
leeleolay/dielectrics
Pushing the Pareto front of band gap and permittivity with ML-guided dielectric materials discovery incl. experimental synthesis and characterization.
leeleolay/DiffCSP
leeleolay/DiffCSP-PP
[ICLR 2024] The implementation for the paper "Space Group Constrained Crystal Generation"
leeleolay/DIG
A library for graph deep learning research
leeleolay/Graphormer
Graphormer is a general-purpose deep learning backbone for molecular modeling.
leeleolay/jax-md
Differentiable, Hardware Accelerated, Molecular Dynamics
leeleolay/KPGT
codes for KPGT (Knowledge-guided Pre-training of Graph Transformer)
leeleolay/lammps
Public development project of the LAMMPS MD software package
leeleolay/LAMMPS_MESO_CPU
leeleolay/DiGress
code for the paper "DiGress: Discrete Denoising diffusion for graph generation"
leeleolay/ferminet
An implementation of the Fermionic Neural Network for ab-initio electronic structure calculations
leeleolay/LAMMPS_MESO_GPU
leeleolay/M2Hub
leeleolay/materials_discovery
leeleolay/matsciml
Open MatSci ML Toolkit is a framework for prototyping and scaling out deep learning models for materials discovery supporting widely used materials science datasets, and built on top of PyTorch Lightning, the Deep Graph Library, and PyTorch Geometric.
leeleolay/mattergen
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property constraints.
leeleolay/MLHessian-TSopt
leeleolay/PaddleMIX
Paddle Multimodal Integration and eXploration, supporting mainstream multi-modal tasks, including end-to-end large-scale multi-modal pretrain models and diffusion model toolbox. Equipped with high performance and flexibility.
leeleolay/PaddleScience
PaddleScience is SDK and library for developing AI-driven scientific computing applications based on PaddlePaddle.
leeleolay/schnetpack
SchNetPack - Deep Neural Networks for Atomistic Systems
leeleolay/Toolkit4MesoCellModel
creat cell model which is used by mesocale viscoelastic membrane model
leeleolay/Transformer-M
[ICLR 2023] One Transformer Can Understand Both 2D & 3D Molecular Data (official implementation)
leeleolay/VAE-DFT
leeleolay/WyCryst
Wyckoff Inorganic Crystal Generator Framework