graph-classification
There are 96 repositories under graph-classification topic.
benedekrozemberczki/awesome-graph-classification
A collection of important graph embedding, classification and representation learning papers with implementations.
THUDM/CogDL
CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)
benedekrozemberczki/awesome-fraud-detection-papers
A curated list of data mining papers about fraud detection.
benedekrozemberczki/CapsGNN
A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).
benedekrozemberczki/SimGNN
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).
daiquocnguyen/Graph-Transformer
Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)
ysig/GraKeL
A scikit-learn compatible library for graph kernels
benedekrozemberczki/APPNP
A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).
cszhangzhen/HGP-SL
Hierarchical Graph Pooling with Structure Learning
bknyaz/graph_nn
Graph Classification with Graph Convolutional Networks in PyTorch (NeurIPS 2018 Workshop)
gasteigerjo/ppnp
PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)
TrustAGI-Lab/graph_datasets
A Repository of Benchmark Graph Datasets for Graph Classification (31 Graph Datasets In Total).
benedekrozemberczki/GAM
A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).
benedekrozemberczki/SEAL-CI
A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)
BorgwardtLab/TOGL
Topological Graph Neural Networks (ICLR 2022)
LiuChuang0059/graph-pooling-papers
IJCAI‘23 Survey Track: Papers on Graph Pooling (GNN-Pooling)
JinheonBaek/GMT
Official Code Repository for the paper "Accurate Learning of Graph Representations with Graph Multiset Pooling" (ICLR 2021)
BorgwardtLab/GraphKernels
A package for computing Graph Kernels
malllabiisc/ASAP
AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
giannisnik/cnn-graph-classification
A convolutional neural network for graph classification in PyTorch
leftthomas/DGCNN
A PyTorch implementation of DGCNN based on AAAI 2018 paper "An End-to-End Deep Learning Architecture for Graph Classification"
BorgwardtLab/P-WL
A Persistent Weisfeiler–Lehman Procedure for Graph Classification
yangnianzu0515/MoleOOD
Official implementation for the paper "Learning Substructure Invariance for Out-of-Distribution Molecular Representations" (NeurIPS 2022).
benedekrozemberczki/PDN
The official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21)
ZhenyuYangMQ/Awesome-Graph-Level-Learning
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…
giannisnik/rwgnn
Random Walk Graph Neural Networks
harryjo97/EHGNN
Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)
FilippoMB/Benchmark_dataset_for_graph_classification
Dataset for testing graph classification algorithms, such as Graph Kernels and Graph Neural Networks.
safreita1/malnet-graph
A large-scale database for graph representation learning
benedekrozemberczki/FEATHER
The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models".
daiquocnguyen/QGNN
Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)
nphdang/GE-FSG
Graph Embedding via Frequent Subgraphs
bdqnghi/ggnn.tensorflow
Tensorflow implementation of Gated Graph Neural Network for Source Code Classification
FilippoMB/Simplifying-Clustering-with-Graph-Neural-Networks
Implementation of "Just Balance GNN" for graph classification and node clustering from the paper "Simplifying Clusterings with Graph Neural Networks".
bayer-science-for-a-better-life/phc-gnn
Implementation of the Paper: "Parameterized Hypercomplex Graph Neural Networks for Graph Classification" by Tuan Le, Marco Bertolini, Frank Noé and Djork-Arné Clevert
ashleve/graph_classification
Benchmarking GNNs with PyTorch Lightning: Open Graph Benchmarks and image classification from superpixels