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 776–800 of 927 papers

Title	Date	Tasks	Status	Hype
Learning Universal Graph Neural Network Embeddings With Aid Of Transfer Learning	Sep 22, 2019	DecoderGraph Classification	CodeCode Available	0
A Non-Negative Factorization approach to node pooling in Graph Convolutional Neural Networks	Sep 7, 2019	Graph Classification	—Unverified	0
NEAR: Neighborhood Edge AggregatoR for Graph Classification	Sep 6, 2019	ClassificationGeneral Classification	—Unverified	0
Deep Weisfeiler-Lehman Assignment Kernels via Multiple Kernel Learning	Aug 19, 2019	General ClassificationGraph Classification	—Unverified	0
Invariant embedding for graph classification	Aug 18, 2019	ClassificationGeneral Classification	—Unverified	0
CensNet: Convolution with Edge-Node Switching in Graph Neural Networks	Aug 10, 2019	Graph ClassificationGraph Embedding	—Unverified	0
HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction	Aug 7, 2019	Graph AttentionGraph Classification	CodeCode Available	0
Graph Neural Networks for Small Graph and Giant Network Representation Learning: An Overview	Aug 1, 2019	Graph ClassificationGraph Neural Network	—Unverified	0
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization	Jul 31, 2019	Graph ClassificationMolecular Property Prediction	CodeCode Available	1
IsoNN: Isomorphic Neural Network for Graph Representation Learning and Classification	Jul 22, 2019	ClassificationGeneral Classification	CodeCode Available	0
Topology Based Scalable Graph Kernels	Jul 15, 2019	Graph Classification	—Unverified	0
k-hop Graph Neural Networks	Jul 13, 2019	General ClassificationGraph Classification	CodeCode Available	0
Semi-Supervised Graph Embedding for Multi-Label Graph Node Classification	Jul 12, 2019	ClassificationGeneral Classification	—Unverified	0
Label-Aware Graph Convolutional Networks	Jul 10, 2019	ClassificationGeneral Classification	—Unverified	0
Graph Representation Learning via Hard and Channel-Wise Attention Networks	Jul 5, 2019	Graph AttentionGraph Classification	CodeCode Available	0
Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation	Jul 4, 2019	Graph ClassificationGraph Representation Learning	CodeCode Available	0
iPool -- Information-based Pooling in Hierarchical Graph Neural Networks	Jul 1, 2019	Graph Classification	—Unverified	0
Spectral Clustering with Graph Neural Networks for Graph Pooling	Jun 30, 2019	ClusteringGraph Classification	CodeCode Available	1
Graph Star Net for Generalized Multi-Task Learning	Jun 21, 2019	ClassificationGeneral Classification	CodeCode Available	0
Attacking Graph Convolutional Networks via Rewiring	Jun 10, 2019	General ClassificationGraph Classification	—Unverified	0
A Persistent Weisfeiler–Lehman Procedure for Graph Classification	Jun 9, 2019	ClassificationGeneral Classification	CodeCode Available	0
Labeled Graph Generative Adversarial Networks	Jun 7, 2019	Graph ClassificationImage Generation	—Unverified	0
DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification	Jun 5, 2019	General ClassificationGraph Classification	CodeCode Available	0
GOT: An Optimal Transport framework for Graph comparison	Jun 5, 2019	Graph Classification	CodeCode Available	1
Wasserstein Weisfeiler-Lehman Graph Kernels	Jun 4, 2019	Graph Classification	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