A collection of important graph embedding, classification and representation learning papers with implementations.

CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)

A curated list of data mining papers about fraud detection.

A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).

A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).

Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)

A scikit-learn compatible library for graph kernels

A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).

Graph Classification with Graph Convolutional Networks in PyTorch (NeurIPS 2018 Workshop)

PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)

Hierarchical Graph Pooling with Structure Learning

A Repository of Benchmark Graph Datasets for Graph Classification (31 Graph Datasets In Total).

A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)

Topological Graph Neural Networks (ICLR 2022)

A package for computing Graph Kernels

AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

Papers on Graph Pooling (GNN-Pooling)

Official Code Repository for the paper "Accurate Learning of Graph Representations with Graph Multiset Pooling" (ICLR 2021)

A convolutional neural network for graph classification in PyTorch