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 51–75 of 927 papers

Title	Date	Tasks	Status	Hype
Enhance Information Propagation for Graph Neural Network by Heterogeneous Aggregations	Feb 8, 2021	Graph ClassificationGraph Neural Network	CodeCode Available	1
Evaluating Modules in Graph Contrastive Learning	Jun 15, 2021	Contrastive LearningGraph Classification	CodeCode Available	1
Adversarial Attack on Community Detection by Hiding Individuals	Jan 22, 2020	Adversarial AttackCommunity Detection	CodeCode Available	1
Approximate Network Motif Mining Via Graph Learning	Jun 2, 2022	BIG-bench Machine LearningGraph Classification	CodeCode Available	1
A Fair Comparison of Graph Neural Networks for Graph Classification	Dec 20, 2019	General ClassificationGraph Classification	CodeCode Available	1
Boosting Graph Structure Learning with Dummy Nodes	Jun 17, 2022	Graph ClassificationGraph Representation Learning	CodeCode Available	1
A Generalization of ViT/MLP-Mixer to Graphs	Dec 27, 2022	Graph ClassificationGraph Regression	CodeCode Available	1
Fake News Detection on Social Media using Geometric Deep Learning	Feb 10, 2019	Common Sense ReasoningDeep Learning	CodeCode Available	1
Agent-based Graph Neural Networks	Jun 22, 2022	Graph ClassificationGraph Neural Network	CodeCode Available	1
Federated Graph Classification over Non-IID Graphs	Jun 25, 2021	ClassificationClustering	CodeCode Available	1
Few-Shot Learning on Graphs via Super-Classes based on Graph Spectral Measures	Feb 27, 2020	Active LearningClassification	CodeCode Available	1
Fine-tuning Graph Neural Networks by Preserving Graph Generative Patterns	Dec 21, 2023	Graph ClassificationGraph Learning	CodeCode Available	1
Directional Graph Networks	Oct 6, 2020	Data AugmentationGraph Classification	CodeCode Available	1
Discovering Invariant Rationales for Graph Neural Networks	Jan 30, 2022	Graph Classification	CodeCode Available	1
A Meta-Learning Approach for Training Explainable Graph Neural Networks	Sep 20, 2021	Graph ClassificationMeta-Learning	CodeCode Available	1
Causal Attention for Interpretable and Generalizable Graph Classification	Dec 30, 2021	ClassificationGraph Attention	CodeCode Available	1
Deep Graph Mapper: Seeing Graphs through the Neural Lens	Feb 10, 2020	Graph ClassificationGraph Representation Learning	CodeCode Available	1
Convolutional Kernel Networks for Graph-Structured Data	Mar 11, 2020	Graph Classification	CodeCode Available	1
AutoRDF2GML: Facilitating RDF Integration in Graph Machine Learning	Jul 26, 2024	Graph ClassificationKnowledge Graphs	CodeCode Available	1
Automatic Relation-aware Graph Network Proliferation	May 31, 2022	Graph ClassificationGraph Learning	CodeCode Available	1
Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation	May 24, 2022	Graph ClassificationKnowledge Distillation	CodeCode Available	1
COPT: Coordinated Optimal Transport for Graph Sketching	Mar 9, 2020	Graph Classification	CodeCode Available	1
Contrastive Multi-View Representation Learning on Graphs	Jun 10, 2020	General ClassificationGraph Classification	CodeCode Available	1
Convergent Graph Solvers	Jun 3, 2021	Graph ClassificationGraph Neural Network	CodeCode Available	1
Detecting Beneficial Feature Interactions for Recommender Systems	Aug 2, 2020	Graph ClassificationGraph Neural Network	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