There are 6 repositories under graph-deep-learning topic.
Repository for benchmarking graph neural networks
Graph Neural Networks with Keras and Tensorflow 2.
Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.
Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)
Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
Android Malware Detection with Graph Convolutional Networks using Function Call Graph and its Derivatives.
An unofficial implementation of Graph Transformer (Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification) - IJCAI 2021
slientruss3d : Python for stable truss analysis and optimization tool
NLP - Semantic Role Labeling using GCN, Bert and Biaffine Attention Layer. Developed in Pytorch
An attempt at demystifying graph deep learning
Tumor2Graph: a novel Overall-Tumor-Profile-derived virtual graph deep learning for predicting tumor typing and subtyping.
A repo for baseline of graph pooling.
Antibiotic discovery using graph deep learning, with Chemprop.
Deep Learning with Graph Representation of Bio-Molecules to estimate physical Properties
Source code and data of the paper entitled "iACP-GCR: Identifying multi-target anticancer compounds using multitask learning on graph convolutional residual neural networks"
Final assignment of EE226 course in SJTU by Group 12
Non markovian extension to the graph edit network model proposed by Paassen et al.