There are 21 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).
Hierarchical Graph Pooling with Structure Learning
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)
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)
A collection of graph foundation models including papers, codes, and datasets.
Topological Graph Neural Networks (ICLR 2022)
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)
A package for computing Graph Kernels
AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
A convolutional neural network for graph classification in PyTorch
A PyTorch implementation of DGCNN based on AAAI 2018 paper "An End-to-End Deep Learning Architecture for Graph Classification"
A Persistent Weisfeiler–Lehman Procedure for Graph Classification
Official implementation for the paper "Learning Substructure Invariance for Out-of-Distribution Molecular Representations" (NeurIPS 2022).
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…
The official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21)
Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)
A large-scale database for graph representation learning
Dataset for testing graph classification algorithms, such as Graph Kernels and Graph Neural Networks.
The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models".
Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)
Tensorflow implementation of Gated Graph Neural Network for Source Code Classification
Implementation of "Just Balance GNN" for graph classification and node clustering from the paper "Simplifying Clusterings with Graph Neural Networks".
Implementation of the Paper: "Parameterized Hypercomplex Graph Neural Networks for Graph Classification" by Tuan Le, Marco Bertolini, Frank Noé and Djork-Arné Clevert