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 401–425 of 927 papers

Title	Date	Tasks	Status	Hype
Template based Graph Neural Network with Optimal Transport Distances	May 31, 2022	Graph ClassificationGraph Matching	CodeCode Available	0
Automatic Relation-aware Graph Network Proliferation	May 31, 2022	Graph ClassificationGraph Learning	CodeCode Available	1
CGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning	May 30, 2022	Collaborative FilteringGraph Classification	CodeCode Available	0
Recipe for a General, Powerful, Scalable Graph Transformer	May 25, 2022	Graph ClassificationGraph Property Prediction	CodeCode Available	2
High-Order Pooling for Graph Neural Networks with Tensor Decomposition	May 24, 2022	ClassificationGraph Classification	—Unverified	0
Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation	May 24, 2022	Graph ClassificationKnowledge Distillation	CodeCode Available	1
Asynchronous Neural Networks for Learning in Graphs	May 24, 2022	Distributed ComputingGraph Classification	—Unverified	0
GraphMAE: Self-Supervised Masked Graph Autoencoders	May 22, 2022	Contrastive LearningGraph Classification	CodeCode Available	2
KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification	May 21, 2022	Graph ClassificationGraph Neural Network	—Unverified	0
Towards Explanation for Unsupervised Graph-Level Representation Learning	May 20, 2022	Decision MakingGraph Classification	CodeCode Available	2
Representation Power of Graph Neural Networks: Improved Expressivity via Algebraic Analysis	May 19, 2022	Graph Classification	—Unverified	0
Label-invariant Augmentation for Semi-Supervised Graph Classification	May 19, 2022	ClassificationContrastive Learning	—Unverified	0
Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency Analysis	May 19, 2022	Graph ClassificationLink Prediction	—Unverified	0
GraphHD: Efficient graph classification using hyperdimensional computing	May 16, 2022	ClassificationGraph Classification	CodeCode Available	1
Orthogonal Gromov-Wasserstein Discrepancy with Efficient Lower Bound	May 12, 2022	Graph Classification	CodeCode Available	0
NDGGNET-A Node Independent Gate based Graph Neural Networks	May 11, 2022	Graph ClassificationLink Prediction	—Unverified	0
Spatial-temporal associations representation and application for process monitoring using graph convolution neural network	May 11, 2022	Chemical ProcessGraph Classification	—Unverified	0
Data-Free Adversarial Knowledge Distillation for Graph Neural Networks	May 8, 2022	Generative Adversarial NetworkGraph Classification	—Unverified	0
Bandits for Structure Perturbation-based Black-box Attacks to Graph Neural Networks with Theoretical Guarantees	May 7, 2022	Graph ClassificationNode Classification	CodeCode Available	0
Clustered Graph Matching for Label Recovery and Graph Classification	May 6, 2022	ClassificationGraph Classification	—Unverified	0
Spiking Graph Convolutional Networks	May 5, 2022	Graph ClassificationRecommendation Systems	CodeCode Available	1
FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs	May 5, 2022	ClassificationFew-Shot Learning	CodeCode Available	1
HL-Net: Heterophily Learning Network for Scene Graph Generation	May 3, 2022	Graph ClassificationGraph Generation	CodeCode Available	1
FastGCL: Fast Self-Supervised Learning on Graphs via Contrastive Neighborhood Aggregation	May 2, 2022	ClassificationContrastive Learning	—Unverified	0
DOTIN: Dropping Task-Irrelevant Nodes for GNNs	Apr 28, 2022	Graph ClassificationGraph Learning	CodeCode Available	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