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 226–250 of 927 papers

Title	Date	Tasks	Status	Hype
A Fair Comparison of Graph Neural Networks for Graph Classification	Dec 20, 2019	General ClassificationGraph Classification	CodeCode Available	1
Global Counterfactual Explainer for Graph Neural Networks	Oct 21, 2022	counterfactualCounterfactual Explanation	CodeCode Available	1
Transforming PageRank into an Infinite-Depth Graph Neural Network	Jul 1, 2022	Graph ClassificationGraph Neural Network	CodeCode Available	1
Edge Representation Learning with Hypergraphs	Jun 30, 2021	Graph ClassificationGraph Reconstruction	CodeCode Available	1
Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural Networks	Oct 4, 2022	Graph Classification	CodeCode Available	1
Parameterized Hypercomplex Graph Neural Networks for Graph Classification	Mar 30, 2021	ClassificationGeneral Classification	CodeCode Available	1
Graph2Graph Learning with Conditional Autoregressive Models	Jun 6, 2021	Graph ClassificationGraph Learning	—Unverified	0
A Comparison of Graph Neural Networks for Malware Classification	Mar 22, 2023	ClassificationGraph Classification	—Unverified	0
Graph Neural Network-based Spectral Filtering Mechanism for Imbalance Classification in Network Digital Twin	Feb 17, 2025	Graph ClassificationGraph Neural Network	—Unverified	0
Gradient Inversion Attack on Graph Neural Networks	Nov 29, 2024	Federated LearningGraph Classification	—Unverified	0
Graffe: Graph Representation Learning via Diffusion Probabilistic Models	May 8, 2025	DenoisingGraph Classification	—Unverified	0
Graph Adversarial Self-Supervised Learning	Dec 1, 2021	Graph ClassificationSelf-Supervised Learning	—Unverified	0
A Semantic and Clean-label Backdoor Attack against Graph Convolutional Networks	Mar 19, 2025	Backdoor AttackGraph Classification	—Unverified	0
A semantic backdoor attack against Graph Convolutional Networks	Feb 28, 2023	Backdoor AttackClassification	—Unverified	0
GQWformer: A Quantum-based Transformer for Graph Representation Learning	Dec 3, 2024	Graph ClassificationGraph Representation Learning	—Unverified	0
ENADPool: The Edge-Node Attention-based Differentiable Pooling for Graph Neural Networks	May 16, 2024	Graph Classification	—Unverified	0
Empowering Graph Representation Learning with Paired Training and Graph Co-Attention	Sep 25, 2019	Graph ClassificationGraph Neural Network	—Unverified	0
EMP: Effective Multidimensional Persistence for Graph Representation Learning	Jan 24, 2024	Graph ClassificationGraph Representation Learning	—Unverified	0
Ego-based Entropy Measures for Structural Representations on Graphs	Feb 17, 2021	Graph Classification	—Unverified	0
CiliaGraph: Enabling Expression-enhanced Hyper-Dimensional Computation in Ultra-Lightweight and One-Shot Graph Classification on Edge	May 29, 2024	Computational EfficiencyGraph Classification	—Unverified	0
Graph Anomaly Detection with Graph Neural Networks: Current Status and Challenges	Sep 29, 2022	Anomaly DetectionGraph Anomaly Detection	—Unverified	0
Enhancing High-Energy Particle Physics Collision Analysis through Graph Data Attribution Techniques	Jul 20, 2024	Graph ClassificationGraph Neural Network	—Unverified	0
Classification by Attention: Scene Graph Classification with Prior Knowledge	Nov 19, 2020	ClassificationGeneral Classification	—Unverified	0
EPIC: Graph Augmentation with Edit Path Interpolation via Learnable Cost	Jun 2, 2023	Data AugmentationGraph Classification	—Unverified	0
Ego-based Entropy Measures for Structural Representations	Mar 1, 2020	General ClassificationGraph Classification	—Unverified	0

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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	δ-2-LWL	Accuracy	85.5	—	Unverified
9	DUGNN	Accuracy	85.5	—	Unverified
10	CIN++	Accuracy	85.3	—	Unverified