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 601–625 of 927 papers

Title	Date	Tasks	Status	Hype
Learning Parametrised Graph Shift Operators	Jan 25, 2021	Graph ClassificationGraph Neural Network	CodeCode Available	0
SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism	Jan 20, 2021	Graph ClassificationGraph Neural Network	CodeCode Available	1
GraphAttacker: A General Multi-Task GraphAttack Framework	Jan 18, 2021	General ClassificationGenerative Adversarial Network	CodeCode Available	0
Membership Inference Attack on Graph Neural Networks	Jan 17, 2021	Graph ClassificationInference Attack	CodeCode Available	1
Label Contrastive Coding based Graph Neural Network for Graph Classification	Jan 14, 2021	ClassificationContrastive Learning	CodeCode Available	1
Optimisation of Spectral Wavelets for Persistence-based Graph Classification	Jan 10, 2021	ClassificationGeneral Classification	—Unverified	0
The Shapley Value of Classifiers in Ensemble Games	Jan 6, 2021	ClassificationEnsemble Pruning	CodeCode Available	1
GraphSAD: Learning Graph Representations with Structure-Attribute Disentanglement	Jan 1, 2021	AttributeDisentanglement	—Unverified	0
Graph Pooling by Edge Cut	Jan 1, 2021	General ClassificationGraph Classification	—Unverified	0
TopoTER: Unsupervised Learning of Topology Transformation Equivariant Representations	Jan 1, 2021	Graph Classification	—Unverified	0
Neural Pooling for Graph Neural Networks	Jan 1, 2021	ClassificationGeneral Classification	—Unverified	0
Graph Structural Aggregation for Explainable Learning	Jan 1, 2021	ClassificationGeneral Classification	—Unverified	0
Bridging Graph Network to Lifelong Learning with Feature Interaction	Jan 1, 2021	Graph ClassificationLifelong learning	—Unverified	0
Learning from multiscale wavelet superpixels using GNN with spatially heterogeneous pooling	Jan 1, 2021	General ClassificationGraph Classification	—Unverified	0
Graph-Graph Similarity Network	Jan 1, 2021	ClassificationGeneral Classification	—Unverified	0
One Vertex Attack on Graph Neural Networks-based Spatiotemporal Forecasting	Jan 1, 2021	Graph Classification	—Unverified	0
On Single-environment Extrapolations in Graph Classification and Regression Tasks	Jan 1, 2021	Classificationcounterfactual	—Unverified	0
Polynomial Graph Convolutional Networks	Jan 1, 2021	Graph ClassificationGraph Neural Network	—Unverified	0
Multi-level Graph Matching Networks for Deep and Robust Graph Similarity Learning	Jan 1, 2021	Graph ClassificationGraph Matching	—Unverified	0
LookHops: light multi-order convolution and pooling for graph classification	Dec 28, 2020	ClassificationGeneral Classification	—Unverified	0
Power Normalizations in Fine-grained Image, Few-shot Image and Graph Classification	Dec 27, 2020	Few-Shot LearningGeneral Classification	—Unverified	0
On Using Classification Datasets to Evaluate Graph-Level Outlier Detection: Peculiar Observations and New Insights	Dec 23, 2020	Binary ClassificationGeneral Classification	CodeCode Available	1
An Experimental Study of the Transferability of Spectral Graph Networks	Dec 18, 2020	BenchmarkingGeneral Classification	CodeCode Available	0
Hierarchical Graph Capsule Network	Dec 16, 2020	Graph Classification	CodeCode Available	1
Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs	Dec 12, 2020	Adversarial AttackGraph 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	DUGNN	Accuracy	85.5	—	Unverified
9	δ-2-LWL	Accuracy	85.5	—	Unverified
10	CIN++	Accuracy	85.3	—	Unverified