Pinned Repositories
AIRS
Artificial Intelligence Research for Science (AIRS)
DIG
A library for graph deep learning research
AIRS
Artificial Intelligence Research for Science (AIRS)
alignn
Atomistic Line Graph Neural Network
cdvae
An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]
crystal-text-llm
Large language models to generate stable crystals.
DIG
A library for graph deep learning research
e3_diffusion_for_molecules
fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Matformer
Official code for Periodic Graph Transformers for Crystal Material Property Prediction (NeurIPS 2022)
YKQ98's Repositories
YKQ98/Matformer
Official code for Periodic Graph Transformers for Crystal Material Property Prediction (NeurIPS 2022)
YKQ98/e3_diffusion_for_molecules
YKQ98/crystal-text-llm
Large language models to generate stable crystals.
YKQ98/AIRS
Artificial Intelligence Research for Science (AIRS)
YKQ98/alignn
Atomistic Line Graph Neural Network
YKQ98/cdvae
An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]
YKQ98/DIG
A library for graph deep learning research
YKQ98/fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
YKQ98/GeoDiff
Implementation of GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation (ICLR 2022).
YKQ98/IMMagician
YKQ98/jarvis
JARVIS-Tools: an open-source software package for data-driven atomistic materials design
YKQ98/jarvis_leaderboard
This project provides benchmark-performances for materials science applications including Artificial Intelligence (AI), Electronic Structure (ES), Force-field (FF), Quantum Computation (QC) and Experiments (EXP) methods.
YKQ98/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
YKQ98/M2Hub
YKQ98/m3gnet
Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.
YKQ98/mace
MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.
YKQ98/pymatgen
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.
YKQ98/pytorch_geometric
Graph Neural Network Library for PyTorch
YKQ98/score_sde
Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
YKQ98/WiseKeep
Wise Keep--Java programming class project