Graph Classification

Graph Classification is a task that involves classifying a graph-structured data into different classes or categories. Graphs are a powerful way to represent relationships and interactions between different entities, and graph classification can be applied to a wide range of applications, such as social network analysis, bioinformatics, and recommendation systems. In graph classification, the input is a graph, and the goal is to learn a classifier that can accurately predict the class of the graph.

( Image credit: Hierarchical Graph Pooling with Structure Learning )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 201–225 of 927 papers

Title	Date	Tasks	Status	Hype
Anonymous Walk Embeddings	May 30, 2018	General ClassificationGraph Classification	CodeCode Available	1
Fast Graph Kernel with Optical Random Features	Oct 16, 2020	Graph Classification	CodeCode Available	1
Fewer is More: A Deep Graph Metric Learning Perspective Using Fewer Proxies	Oct 26, 2020	General ClassificationGraph Classification	CodeCode Available	1
Strategies for Pre-training Graph Neural Networks	May 29, 2019	Graph ClassificationMolecular Property Prediction	CodeCode Available	1
Federated Graph Classification over Non-IID Graphs	Jun 25, 2021	ClassificationClustering	CodeCode Available	1
Fast Graph Representation Learning with PyTorch Geometric	Mar 6, 2019	GPUGraph Classification	CodeCode Available	1
Edge Representation Learning with Hypergraphs	Jun 30, 2021	Graph ClassificationGraph Reconstruction	CodeCode Available	1
Fine-tuning Graph Neural Networks by Preserving Graph Generative Patterns	Dec 21, 2023	Graph ClassificationGraph Learning	CodeCode Available	1
Recurrent Distance Filtering for Graph Representation Learning	Dec 3, 2023	Graph ClassificationGraph Representation Learning	CodeCode Available	1
Regularized Optimal Transport Layers for Generalized Global Pooling Operations	Dec 13, 2022	Graph Classificationimage-classification	CodeCode Available	1
Robust Optimization as Data Augmentation for Large-scale Graphs	Oct 19, 2020	Data AugmentationGraph Classification	CodeCode Available	1
Representing Long-Range Context for Graph Neural Networks with Global Attention	Jan 21, 2022	Graph ClassificationGraph Embedding	CodeCode Available	1
Fine-Tuning Graph Neural Networks via Graph Topology induced Optimal Transport	Mar 20, 2022	Graph ClassificationGraph Learning	CodeCode Available	1
Geodesic Graph Neural Network for Efficient Graph Representation Learning	Oct 6, 2022	Graph ClassificationGraph Learning	CodeCode Available	1
DPPIN: A Biological Repository of Dynamic Protein-Protein Interaction Network Data	Jul 5, 2021	AttributeDrug Discovery	CodeCode Available	1
TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender Systems	Aug 28, 2023	Collaborative FilteringGraph Classification	CodeCode Available	1
DRew: Dynamically Rewired Message Passing with Delay	May 13, 2023	Graph ClassificationGraph Regression	CodeCode Available	1
DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks	Nov 11, 2021	Graph ClassificationGraph Regression	CodeCode Available	1
Approximate Network Motif Mining Via Graph Learning	Jun 2, 2022	BIG-bench Machine LearningGraph Classification	CodeCode Available	1
Shortest Path Networks for Graph Property Prediction	Jun 2, 2022	Graph ClassificationGraph Neural Network	CodeCode Available	1
graph2vec: Learning Distributed Representations of Graphs	Jul 17, 2017	ClusteringGeneral Classification	CodeCode Available	1
Simplifying Subgraph Representation Learning for Scalable Link Prediction	Jan 29, 2023	Graph ClassificationGraph Learning	CodeCode Available	1
Graph-level Representation Learning with Joint-Embedding Predictive Architectures	Sep 27, 2023	Contrastive LearningData Augmentation	CodeCode Available	1
On Using Classification Datasets to Evaluate Graph-Level Outlier Detection: Peculiar Observations and New Insights	Dec 23, 2020	Binary ClassificationGeneral Classification	CodeCode Available	1
User Preference-aware Fake News Detection	Apr 25, 2021	Fact CheckingFake News Detection	CodeCode Available	1

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All datasets PROTEINS MUTAG NCI1 D&D ENZYMES IMDb-B COLLAB PTC IMDb-M NCI109 CIFAR10 100k REDDIT-B

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	GIN-0	Accuracy	762	—	Unverified
2	HGP-SL	Accuracy	84.91	—	Unverified
3	rLap (unsupervised)	Accuracy	84.3	—	Unverified
4	TFGW ADJ (L=2)	Accuracy	82.9	—	Unverified
5	FIT-GNN	Accuracy	82.1	—	Unverified
6	DUGNN	Accuracy	81.7	—	Unverified
7	MEWISPool	Accuracy	80.71	—	Unverified
8	CIN++	Accuracy	80.5	—	Unverified
9	MAGPool	Accuracy	80.36	—	Unverified
10	SAEPool	Accuracy	80.36	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Evolution of Graph Classifiers	Accuracy	100	—	Unverified
2	MEWISPool	Accuracy	96.66	—	Unverified
3	TFGW ADJ (L=2)	Accuracy	96.4	—	Unverified
4	GIUNet	Accuracy	95.7	—	Unverified
5	G_Inception	Accuracy	95	—	Unverified
6	GIC	Accuracy	94.44	—	Unverified
7	CIN++	Accuracy	94.4	—	Unverified
8	sGIN	Accuracy	94.14	—	Unverified
9	CAN	Accuracy	94.1	—	Unverified
10	Deep WL SGN(0,1,2)	Accuracy	93.68	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TFGW ADJ (L=2)	Accuracy	88.1	—	Unverified
2	WKPI-kmeans	Accuracy	87.2	—	Unverified
3	FGW wl h=4 sp	Accuracy	86.42	—	Unverified
4	WL-OA Kernel	Accuracy	86.1	—	Unverified
5	WL-OA	Accuracy	86.1	—	Unverified
6	FGW wl h=2 sp	Accuracy	85.82	—	Unverified
7	WWL	Accuracy	85.75	—	Unverified
8	DUGNN	Accuracy	85.5	—	Unverified
9	δ-2-LWL	Accuracy	85.5	—	Unverified
10	CIN++	Accuracy	85.3	—	Unverified