Xiang, Yan's repositories
Chem-Graph-Kernel-Machine
Machine Learning using marginalized graph kernel for chemical molecules.
MD_Analysis
Molecular Dynamics Trajectory Analysis
Molecular_ML
machine learning for chemical compounds
Active-Learning-HESOs
Active learning for High-Entropy-Spinel-Oxides Discovery
chemprop
Message Passing Neural Networks for Molecule Property Prediction
chemicalx
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
descriptastorus
Descriptor computation(chemistry) and (optional) storage for machine learning
graph-attribution
Codebase for Evaluating Attribution for Graph Neural Networks.
GraphGPS
Recipe for a General, Powerful, Scalable Graph Transformer
grover
This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data
MolALKit
Benchmark for molecular active learning.
MolCLR
Implementation of MolCLR: "Molecular Contrastive Learning of Representations via Graph Neural Networks" in PyG.
MolGpKa
The graph-convolutional neural network for pka prediction
nequip
NequIP is a code for building E(3)-equivariant interatomic potentials
pytorch_geometric
Graph Neural Network Library for PyTorch
QuantumDeepField_molecule
Quantum deep field for molecule
REINVENT4
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
rexgen_direct
Template-free prediction of organic reaction outcomes
rogi
Measures of roughness for molecular property landscapes
SJTUThesis
上海交通大学 XeLaTeX 学位论文及课程论文模板 | Shanghai Jiao Tong University XeLaTeX Thesis Template
Tartarus
A Benchmarking Platform for Realistic And Practical Inverse Molecular Design
xaibench_tf
Supporting models and data to doi 10.33774/chemrxiv-2021-pp88m