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 576–600 of 927 papers

Title	Date	Tasks	Status
Quantifying the Intrinsic Usefulness of Attributional Explanations for Graph Neural Networks with Artificial Simulatability Studies	May 25, 2023	Graph Classification	—Unverified
Quantum-based subgraph convolutional neural networks	Apr 1, 2019	General ClassificationGraph Classification	—Unverified
Quantum Graph Convolutional Neural Networks	Jul 7, 2021	Graph Classification	—Unverified
Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs	Dec 12, 2020	Adversarial AttackGraph Classification	—Unverified
RAHNet: Retrieval Augmented Hybrid Network for Long-tailed Graph Classification	Aug 4, 2023	Graph ClassificationRetrieval	—Unverified
Random Walk Graph Neural Networks	Dec 1, 2020	Graph ClassificationGraph Neural Network	—Unverified
Recovering Missing Node Features with Local Structure-based Embeddings	Sep 16, 2023	Graph Classification	—Unverified
Reducing Oversmoothing through Informed Weight Initialization in Graph Neural Networks	Oct 31, 2024	Graph Classification	—Unverified
Reinforcement Learning For Data Poisoning on Graph Neural Networks	Feb 12, 2021	BIG-bench Machine LearningClassification	—Unverified
Relational Reasoning Over Spatial-Temporal Graphs for Video Summarization	Apr 6, 2022	Graph ClassificationRelation	—Unverified
Relation Regularized Scene Graph Generation	Feb 22, 2022	Graph ClassificationGraph Generation	—Unverified
Relaxing Graph Transformers for Adversarial Attacks	Jul 16, 2024	Adversarial RobustnessGraph Classification	—Unverified
RetGK: Graph Kernels based on Return Probabilities of Random Walks	Sep 7, 2018	Computational EfficiencyGeneral Classification	—Unverified
Rethinking the impact of noisy labels in graph classification: A utility and privacy perspective	Jun 11, 2024	ClassificationContrastive Learning	—Unverified
Revisiting 2D Convolutional Neural Networks for Graph-based Applications	May 23, 2021	Computational EfficiencyGraph Classification	—Unverified
Revisiting Adversarial Attacks on Graph Neural Networks for Graph Classification	Aug 13, 2022	ClassificationGraph Classification	—Unverified
Revisiting Graph Neural Networks for Link Prediction	Sep 28, 2020	ClassificationGraph Classification	—Unverified
Revisiting Graph Neural Networks on Graph-level Tasks: Comprehensive Experiments, Analysis, and Improvements	Jan 1, 2025	Contrastive LearningGraph Classification	—Unverified
Revisiting Virtual Nodes in Graph Neural Networks for Link Prediction	Sep 29, 2021	ClusteringGraph Classification	—Unverified
Rhomboid Tiling for Geometric Graph Deep Learning	May 14, 2025	ClusteringDeep Learning	—Unverified
Ring Reservoir Neural Networks for Graphs	May 11, 2020	Graph Classification	—Unverified
Robust Ante-hoc Graph Explainer using Bilevel Optimization	May 25, 2023	AttributeBilevel Optimization	—Unverified
Robust Hierarchical Graph Classification with Subgraph Attention	Jul 19, 2020	ClassificationGeneral Classification	—Unverified
Robustness Inspired Graph Backdoor Defense	Jun 14, 2024	backdoor defenseGraph Classification	—Unverified
Robustness of Graph Classification: failure modes, causes, and noise-resistant loss in Graph Neural Networks	Dec 11, 2024	Graph ClassificationInductive Bias	—Unverified

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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