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 326–350 of 927 papers

Title	Date	Tasks	Status
Defense-as-a-Service: Black-box Shielding against Backdoored Graph Models	Oct 7, 2024	Backdoor AttackClustering	—Unverified
Defending Against Backdoor Attack on Graph Nerual Network by Explainability	Sep 7, 2022	Backdoor AttackGraph Classification	—Unverified
Graph Neural Networks for Inconsistent Cluster Detection in Incremental Entity Resolution	May 12, 2021	Entity ResolutionGraph Classification	—Unverified
Deep Weisfeiler-Lehman Assignment Kernels via Multiple Kernel Learning	Aug 19, 2019	General ClassificationGraph Classification	—Unverified
Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification	Dec 10, 2018	Graph ClassificationGraph Embedding	—Unverified
Bayesian Hyperparameter Optimization with BoTorch, GPyTorch and Ax	Dec 11, 2019	Bayesian OptimizationGaussian Processes	—Unverified
Deep Learning for Molecular Graphs with Tiered Graph Autoencoders and Graph Prediction	Oct 24, 2019	General ClassificationGraph Classification	—Unverified
An End-to-End Graph Convolutional Kernel Support Vector Machine	Feb 29, 2020	ClassificationFeature Engineering	—Unverified
Graph Neural Alchemist: An innovative fully modular architecture for time series-to-graph classification	Oct 12, 2024	Graph ClassificationGraph Neural Network	—Unverified
Deep Graph Reprogramming	Apr 28, 2023	3D Object RecognitionAction Recognition	—Unverified
Bayesian Graph Convolutional Neural Networks Using Non-Parametric Graph Learning	Oct 26, 2019	Bayesian InferenceGeneral Classification	—Unverified
Deep Graph-Level Clustering Using Pseudo-Label-Guided Mutual Information Maximization Network	Feb 5, 2023	ClusteringGraph Classification	—Unverified
Deep Graph Kernels	Aug 10, 2015	Graph ClassificationLanguage Modeling	—Unverified
A Class-Aware Representation Refinement Framework for Graph Classification	Sep 2, 2022	ClassificationGraph Classification	—Unverified
Graph Neural Networks for Small Graph and Giant Network Representation Learning: An Overview	Aug 1, 2019	Graph ClassificationGraph Neural Network	—Unverified
Deep Graph Attention Model	Sep 15, 2017	General ClassificationGraph Attention	—Unverified
Class-Balanced and Reinforced Active Learning on Graphs	Feb 15, 2024	Active LearningGraph Classification	—Unverified
DEEP GEOMETRICAL GRAPH CLASSIFICATION	May 1, 2019	ClassificationClustering	—Unverified
Bayesian Deep Learning for Graphs	Feb 24, 2022	Deep LearningGraph Classification	—Unverified
Graph-based Security and Privacy Analytics via Collective Classification with Joint Weight Learning and Propagation	Dec 4, 2018	AttributeClassification	—Unverified
Graph-Based Neural Network Models with Multiple Self-Supervised Auxiliary Tasks	Nov 14, 2020	Auxiliary LearningGraph Classification	—Unverified
Graph-based Argument Quality Assessment	Sep 1, 2021	Graph Classification	—Unverified
Bandits for Black-box Attacks to Graph Neural Networks with Structure Perturbation	Sep 29, 2021	Graph ClassificationNode Classification	—Unverified
Graph Classification Based on Skeleton and Component Features	Feb 2, 2021	ClassificationGeneral Classification	—Unverified
Graph-Aware Transformer: Is Attention All Graphs Need?	Jun 9, 2020	AllDecoder	—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