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 151–175 of 927 papers

Title	Date	Tasks	Status	Hype
Graph Autoencoder for Graph Compression and Representation Learning	Mar 4, 2021	Data CompressionGraph Classification	CodeCode Available	1
Accurate Learning of Graph Representations with Graph Multiset Pooling	Feb 23, 2021	Graph ClassificationGraph Clustering	CodeCode Available	1
Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing	Feb 17, 2021	Graph ClassificationGraph Learning	CodeCode Available	1
Online Graph Dictionary Learning	Feb 12, 2021	Dictionary LearningGraph Classification	CodeCode Available	1
Enhance Information Propagation for Graph Neural Network by Heterogeneous Aggregations	Feb 8, 2021	Graph ClassificationGraph Neural Network	CodeCode Available	1
[Re] Parameterized Explainer for Graph Neural Network	Jan 31, 2021	Graph ClassificationGraph Neural Network	CodeCode Available	1
Efficient Graph Deep Learning in TensorFlow with tf_geometric	Jan 27, 2021	Deep LearningGeneral Classification	CodeCode Available	1
SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism	Jan 20, 2021	Graph ClassificationGraph Neural Network	CodeCode Available	1
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
The Shapley Value of Classifiers in Ensemble Games	Jan 6, 2021	ClassificationEnsemble Pruning	CodeCode Available	1
On Using Classification Datasets to Evaluate Graph-Level Outlier Detection: Peculiar Observations and New Insights	Dec 23, 2020	Binary ClassificationGeneral Classification	CodeCode Available	1
Hierarchical Graph Capsule Network	Dec 16, 2020	Graph Classification	CodeCode Available	1
Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks	Dec 1, 2020	General ClassificationGraph Classification	CodeCode Available	1
Two-stage Training of Graph Neural Networks for Graph Classification	Nov 10, 2020	ClassificationGeneral Classification	CodeCode Available	1
Parameterized Explainer for Graph Neural Network	Nov 9, 2020	Graph ClassificationGraph Neural Network	CodeCode Available	1
Fewer is More: A Deep Graph Metric Learning Perspective Using Fewer Proxies	Oct 26, 2020	General ClassificationGraph Classification	CodeCode Available	1
Line Graph Neural Networks for Link Prediction	Oct 20, 2020	ClassificationGeneral Classification	CodeCode Available	1
Robust Optimization as Data Augmentation for Large-scale Graphs	Oct 19, 2020	Data AugmentationGraph Classification	CodeCode Available	1
Fast Graph Kernel with Optical Random Features	Oct 16, 2020	Graph Classification	CodeCode Available	1
Graph Information Bottleneck for Subgraph Recognition	Oct 12, 2020	DenoisingGraph Classification	CodeCode Available	1
Factorizable Graph Convolutional Networks	Oct 12, 2020	Graph ClassificationGraph Regression	CodeCode Available	1
Locality Preserving Dense Graph Convolutional Networks with Graph Context-Aware Node Representations	Oct 12, 2020	ClassificationDecoder	CodeCode Available	1
Directional Graph Networks	Oct 6, 2020	Data AugmentationGraph Classification	CodeCode Available	1
Graph Cross Networks with Vertex Infomax Pooling	Oct 5, 2020	ClassificationGeneral Classification	CodeCode Available	1

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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