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 376–400 of 927 papers

Title	Date	Tasks	Status	Score
An Experimental Study of the Transferability of Spectral Graph Networks	Dec 18, 2020	BenchmarkingGeneral Classification	CodeCode Available	5
ImageNet Classification with Deep Convolutional Neural Networks	Dec 1, 2012	General ClassificationGPU	CodeCode Available	5
Graph Filtration Learning	May 27, 2019	General ClassificationGraph Classification	CodeCode Available	5
DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification	Jun 5, 2019	General ClassificationGraph Classification	CodeCode Available	5
Graph Fourier Transformer with Structure-Frequency Information	Apr 28, 2025	Graph ClassificationInductive Bias	CodeCode Available	5
Graph Fuzzy System: Concepts, Models and Algorithms	Oct 30, 2022	Graph ClassificationGraph Clustering	CodeCode Available	5
Density-aware Walks for Coordinated Campaign Detection	Jun 16, 2025	Graph Classification	CodeCode Available	5
Identity Inference on Blockchain using Graph Neural Network	Apr 14, 2021	Graph ClassificationGraph Mining	CodeCode Available	5
Cooperative Classification and Rationalization for Graph Generalization	Mar 10, 2024	ClassificationGraph Classification	CodeCode Available	5
Generalized Simplicial Attention Neural Networks	Sep 5, 2023	Graph ClassificationImputation	CodeCode Available	5
Learning-based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set Matching	Sep 10, 2018	ClusteringCombinatorial Optimization	CodeCode Available	5
Generalization Error of Graph Neural Networks in the Mean-field Regime	Feb 10, 2024	Graph Classification	CodeCode Available	5
A Unified Invariant Learning Framework for Graph Classification	Jan 22, 2025	ClassificationGraph Classification	CodeCode Available	5
Hyperparameter-free and Explainable Whole Graph Embedding	Aug 4, 2021	Graph ClassificationGraph Embedding	CodeCode Available	5
Graph isomorphism UNet	Aug 23, 2023	DecoderGraph Classification	CodeCode Available	5
Imbalanced Graph Classification with Multi-scale Oversampling Graph Neural Networks	May 8, 2024	Graph ClassificationGraph Learning	CodeCode Available	5
Improving the interpretability of GNN predictions through conformal-based graph sparsification	Apr 18, 2024	ClassificationGraph Classification	CodeCode Available	5
GEFL: Extended Filtration Learning for Graph Classification	Jun 4, 2024	ClassificationGraph Classification	CodeCode Available	5
Multi-scale Wasserstein Shortest-path Graph Kernels for Graph Classification	Jun 2, 2022	Graph Classification	CodeCode Available	5
AugWard: Augmentation-Aware Representation Learning for Accurate Graph Classification	Mar 27, 2025	DiversityDrug Discovery	CodeCode Available	5
Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels	Feb 6, 2024	Graph ClassificationGraph Regression	CodeCode Available	5
Higher-order Clustering and Pooling for Graph Neural Networks	Sep 2, 2022	ClusteringGraph Classification	CodeCode Available	5
Higher-Order Message Passing for Glycan Representation Learning	Sep 20, 2024	DiversityGraph Classification	CodeCode Available	5
How Curvature Enhance the Adaptation Power of Framelet GCNs	Jul 19, 2023	Graph ClassificationGraph Neural Network	CodeCode Available	5
Hunt For The Unique, Stable, Sparse And Fast Feature Learning On Graphs	Dec 1, 2017	General ClassificationGraph Classification	CodeCode Available	5

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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