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	Score
A Fair Comparison of Graph Neural Networks for Graph Classification	Dec 20, 2019	General ClassificationGraph Classification	CodeCode Available	1	5
Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-based Similarity	Aug 18, 2023	Graph ClassificationGraph Representation Learning	CodeCode Available	1	5
Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural Networks	Oct 4, 2022	Graph Classification	CodeCode Available	1	5
Edge Representation Learning with Hypergraphs	Jun 30, 2021	Graph ClassificationGraph Reconstruction	CodeCode Available	1	5
Two-stage Training of Graph Neural Networks for Graph Classification	Nov 10, 2020	ClassificationGeneral Classification	CodeCode Available	1	5
Regularized Optimal Transport Layers for Generalized Global Pooling Operations	Dec 13, 2022	Graph Classificationimage-classification	CodeCode Available	1	5
Clique pooling for graph classification	Mar 31, 2019	ClassificationGeneral Classification	CodeCode Available	0	5
CliquePH: Higher-Order Information for Graph Neural Networks through Persistent Homology on Clique Graphs	Sep 12, 2024	Graph ClassificationGraph Learning	CodeCode Available	0	5
A simple yet effective baseline for non-attributed graph classification	Nov 8, 2018	ClassificationComputational Efficiency	CodeCode Available	0	5
Classification of Temporal Graphs using Persistent Homology	Feb 14, 2025	ClassificationGraph Classification	CodeCode Available	0	5
A Simple Baseline Algorithm for Graph Classification	Oct 22, 2018	BIG-bench Machine LearningClassification	CodeCode Available	0	5
How Curvature Enhance the Adaptation Power of Framelet GCNs	Jul 19, 2023	Graph ClassificationGraph Neural Network	CodeCode Available	0	5
Hunt For The Unique, Stable, Sparse And Fast Feature Learning On Graphs	Dec 1, 2017	General ClassificationGraph Classification	CodeCode Available	0	5
PSP: Pre-Training and Structure Prompt Tuning for Graph Neural Networks	Oct 26, 2023	Contrastive LearningGraph Classification	CodeCode Available	0	5
Enhanced Graph Neural Networks with Ego-Centric Spectral Subgraph Embeddings Augmentation	Oct 10, 2023	Graph ClassificationGraph Embedding	CodeCode Available	0	5
Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling	Oct 24, 2019	Graph ClassificationRepresentation Learning	CodeCode Available	0	5
Higher-order Clustering and Pooling for Graph Neural Networks	Sep 2, 2022	ClusteringGraph Classification	CodeCode Available	0	5
Higher-Order Message Passing for Glycan Representation Learning	Sep 20, 2024	DiversityGraph Classification	CodeCode Available	0	5
HyperAggregation: Aggregating over Graph Edges with Hypernetworks	Jul 16, 2024	Graph ClassificationGraph Regression	CodeCode Available	0	5
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations	Nov 18, 2019	ClassificationGeneral Classification	CodeCode Available	0	5
EGC2: Enhanced Graph Classification with Easy Graph Compression	Jul 16, 2021	ClassificationGraph Classification	CodeCode Available	0	5
Harnessing the Power of Large Language Model for Uncertainty Aware Graph Processing	Mar 31, 2024	Graph ClassificationKnowledge Graph Completion	CodeCode Available	0	5
On the Effectiveness of Hybrid Pooling in Mixup-Based Graph Learning for Language Processing	Oct 6, 2022	Code ClassificationData Augmentation	CodeCode Available	0	5
Efficient Mixed Precision Quantization in Graph Neural Networks	May 14, 2025	Graph ClassificationNode Classification	CodeCode Available	0	5
CGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning	May 30, 2022	Collaborative FilteringGraph Classification	CodeCode Available	0	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