zaixizhang Goto Github PK

ans-gt

NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"

awesome-graph-transformer

Papers about graph transformers.

awesome-sbdd

Papers about Structure-based Drug Design (SBDD)

cbd

Official Inplementation of CVPR23 paper "Backdoor Defense via Deconfounded Representation Learning"

cvpr2022-orphicx

Official code for the CVPR 2022 (oral) paper "OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks."

deeprobust

A pytorch adversarial library for attack and defense methods on images and graphs

difflinker

DiffLinker: Equivariant 3D-Conditional Diffusion Model for Molecular Linker Design

diffpure

A new adversarial purification method that uses the forward and reverse processes of diffusion models to remove adversarial perturbations.

diffsbdd

A Euclidean diffusion model for structure-based drug design.

druggps_icml23

Implementation of ICML23 paper "Learning Subpocket Prototypes for Generalizable Structure-based Drug Design"

fair

NeurIPS 2023 Spotlight paper: Full atom protein pocket design via iterative refinement

flag

Implementation of ICLR23 paper "Molecule Generation for Target Protein Binding with Structural Motifs"

fldetector

The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients"

fraggen

This Code is for Fragment-wise 3D Structure-based Molecular Generation with Reliable Geometry

g-schnet

G-SchNet - a generative model for 3d molecular structures

graph-coarsening

Multilevel graph coarsening algorithm with spectral and cut guarantees

graph-mamba

Graph-Mamba: Towards Long-Range Graph Sequence Modelling with Selective State Spaces

graph_transformer

A pytorch implementation of graph transformer for node classification

graphbackdoor

A PyTorch implementation of "Backdoor Attacks to Graph Neural Networks" (SACMAT'21)

graphmi

Official Pytorch implementation of IJCAI'21 paper "GraphMI: Extracting Private Graph Data from Graph Neural Networks"

graphormer

This is the official implementation for "Do Transformers Really Perform Bad for Graph Representation?".

icml18-jtnn

Junction Tree Variational Autoencoder for Molecular Graph Generation (ICML 2018)

mgssl

Official implementation of NeurIPS'21 paper"Motif-based Graph Self-Supervised Learning for Molecular Property Prediction"

mol_opt

molcode

pocket2mol

Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets

pocketgen

Implementation of PocketGen: Generating Full-Atom Ligand-Binding Protein Pockets

powerful-gnns

How Powerful are Graph Neural Networks?

pretrain-gnns

Strategies for Pre-training Graph Neural Networks

pro-gnn

Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"