There are 19 repositories under graph-classification topic.
A collection of important graph embedding, classification and representation learning papers with implementations.
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 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)
Hierarchical Graph Pooling with Structure Learning
PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)
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
IJCAI‘23 Survey Track: Papers on Graph Pooling (GNN-Pooling)
Official Code Repository for the paper "Accurate Learning of Graph Representations with Graph Multiset Pooling" (ICLR 2021)
AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
A convolutional neural network for graph classification in PyTorch
A Persistent Weisfeiler–Lehman Procedure for Graph Classification
A PyTorch implementation of DGCNN based on AAAI 2018 paper "An End-to-End Deep Learning Architecture for Graph Classification"
The official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21)
Official implementation for the paper "Learning Substructure Invariance for Out-of-Distribution Molecular Representations" (NeurIPS 2022).
Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)
Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)
A large-scale database for graph representation learning
Tensorflow implementation of Gated Graph Neural Network for Source Code Classification
The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models".
Awesome graph-level learning methods. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in graph representation learning, graph regression and graph classification to join this project as contribut…
Implementation of the Paper: "Parameterized Hypercomplex Graph Neural Networks for Graph Classification" by Tuan Le, Marco Bertolini, Frank Noé and Djork-Arné Clevert
Benchmarking GNNs with PyTorch Lightning: Open Graph Benchmarks and image classification from superpixels
The released code for the paper: Pooling Architecture Search for Graph Classification, in CIKM 2021.