Node Classification

Node Classification is a machine learning task in graph-based data analysis, where the goal is to assign labels to nodes in a graph based on the properties of nodes and the relationships between them.

Node Classification models aim to predict non-existing node properties (known as the target property) based on other node properties. Typical models used for node classification consists of a large family of graph neural networks. Model performance can be measured using benchmark datasets like Cora, Citeseer, and Pubmed, among others, typically using Accuracy and F1.

( Image credit: Fast Graph Representation Learning With PyTorch Geometric )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1151–1175 of 1860 papers

Title	Date	Tasks	Status	Hype
A Meta-Learning Approach for Training Explainable Graph Neural Networks	Sep 20, 2021	Graph ClassificationMeta-Learning	CodeCode Available	1
Embedding Node Structural Role Identity Using Stress Majorization	Sep 14, 2021	Node Classification	—Unverified	0
HeMI: Multi-view Embedding in Heterogeneous Graphs	Sep 14, 2021	ClusteringLink Prediction	CodeCode Available	0
Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification?	Sep 12, 2021	Inductive BiasNode Classification	—Unverified	0
Ergodic Limits, Relaxations, and Geometric Properties of Random Walk Node Embeddings	Sep 9, 2021	Link PredictionNode Classification	—Unverified	0
QUINT: Node embedding using network hashing	Sep 9, 2021	Link PredictionNetwork Embedding	—Unverified	0
HMSG: Heterogeneous Graph Neural Network based on Metapath Subgraph Learning	Sep 7, 2021	AttributeGraph Neural Network	—Unverified	0
Node Feature Kernels Increase Graph Convolutional Network Robustness	Sep 4, 2021	Node Classification	CodeCode Available	0
An Empirical Study of Graph Contrastive Learning	Sep 2, 2021	Graph ClassificationManagement	CodeCode Available	1
Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations	Aug 31, 2021	Autonomous Drivingimage-classification	—Unverified	0
Heterogeneous Graph Neural Network with Multi-view Representation Learning	Aug 31, 2021	Graph EmbeddingGraph Neural Network	—Unverified	0
Towards Self-Explainable Graph Neural Network	Aug 26, 2021	Graph Neural NetworkNode Classification	CodeCode Available	1
Tree Decomposed Graph Neural Network	Aug 25, 2021	Graph Neural NetworkNode Classification	CodeCode Available	1
Layer-wise Adaptive Graph Convolution Networks Using Generalized Pagerank	Aug 24, 2021	Generalization BoundsNode Classification	—Unverified	0
REFINE: Random RangE FInder for Network Embedding	Aug 24, 2021	Network EmbeddingNode Classification	—Unverified	0
Jointly Learnable Data Augmentations for Self-Supervised GNNs	Aug 23, 2021	Data AugmentationGraph Representation Learning	CodeCode Available	1
A Hard Label Black-box Adversarial Attack Against Graph Neural Networks	Aug 21, 2021	Adversarial AttackClassification	—Unverified	0
Unsupervised Domain-adaptive Hash for Networks	Aug 20, 2021	Link PredictionNode Classification	—Unverified	0
Semi-supervised Network Embedding with Differentiable Deep Quantisation	Aug 20, 2021	Link PredictionNetwork Embedding	—Unverified	0
Blockchain Phishing Scam Detection via Multi-channel Graph Classification	Aug 19, 2021	ClassificationGraph Classification	—Unverified	0
Temporal Graph Network Embedding with Causal Anonymous Walks Representations	Aug 19, 2021	BIG-bench Machine LearningClassification	CodeCode Available	0
Label-informed Graph Structure Learning for Node Classification	Aug 10, 2021	ClassificationGraph structure learning	—Unverified	0
Self-supervised Consensus Representation Learning for Attributed Graph	Aug 10, 2021	Graph Representation LearningNode Classification	CodeCode Available	0
A Framework for Joint Unsupervised Learning of Cluster-Aware Embedding for Heterogeneous Networks	Aug 9, 2021	ClusteringNode Classification	—Unverified	0
Missing Data Estimation in Temporal Multilayer Position-aware Graph Neural Network (TMP-GNN)	Aug 7, 2021	AttributeGraph Neural Network	—Unverified	0

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All datasets Citeseer Pubmed Cora CiteSeer with Public Split: fixed 20 nodes per class PubMed with Public Split: fixed 20 nodes per class Cora with Public Split: fixed 20 nodes per class PPI Coauthor CS Cora (0.5%)Cora (1%)Cora (3%)PubMed (0.03%)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	NodeNet	Accuracy	80.09	—	Unverified
2	SplineCNN	Accuracy	79.2	—	Unverified
3	PathNet	Accuracy (%)	77.98	—	Unverified
4	3ference	Accuracy	76.33	—	Unverified
5	MMA	Accuracy	76.3	—	Unverified
6	PPNP	Accuracy	75.83	—	Unverified
7	CoLinkDist	Accuracy	75.79	—	Unverified
8	CoLinkDistMLP	Accuracy	75.77	—	Unverified
9	APPNP	Accuracy	75.73	—	Unverified
10	Cleora	Accuracy	75.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	NodeNet	Accuracy	90.21	—	Unverified
2	CoLinkDist	Accuracy	89.58	—	Unverified
3	CoLinkDistMLP	Accuracy	89.53	—	Unverified
4	PathNet	Accuracy (%)	88.92	—	Unverified
5	3ference	Accuracy	88.9	—	Unverified
6	SplineCNN	Accuracy	88.88	—	Unverified
7	LinkDist	Accuracy	88.86	—	Unverified
8	LinkDistMLP	Accuracy	88.79	—	Unverified
9	PairE	F1	88.57	—	Unverified
10	GCN + Mixup	Accuracy	87.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LinkDist	Accuracy	88.24	—	Unverified
2	CoLinkDist	Accuracy	87.89	—	Unverified
3	3ference	Accuracy	87.78	—	Unverified
4	LinkDistMLP	Accuracy	87.58	—	Unverified
5	CoLinkDistMLP	Accuracy	87.54	—	Unverified
6	NodeNet	Accuracy	86.8	—	Unverified
7	Cleora	Accuracy	86.8	—	Unverified
8	MMA	Accuracy	85.8	—	Unverified
9	GResNet(GAT)	Accuracy	85.5	—	Unverified
10	TransGNN	1:1 Accuracy	85.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OGC	Accuracy	77.5	—	Unverified
2	LDS-GNN	Accuracy	75	—	Unverified
3	CPF-tra-APPNP	Accuracy	74.6	—	Unverified
4	G3NN	Accuracy	74.5	—	Unverified
5	GEM	Accuracy	74.2	—	Unverified
6	GGCM	Accuracy	74.2	—	Unverified
7	Truncated Krylov	Accuracy	73.86	—	Unverified
8	SSGC	Accuracy	73.6	—	Unverified
9	OKDEEM	Accuracy	73.53	—	Unverified
10	GCNII	Accuracy	73.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OGC	Accuracy	83.4	—	Unverified
2	CPF-tra-GCNII	Accuracy	83.2	—	Unverified
3	DSGCN	Accuracy	81.9	—	Unverified
4	Truncated Krylov	Accuracy	81.7	—	Unverified
5	SuperGAT MX	Accuracy	81.7	—	Unverified
6	G-APPNP	Accuracy	80.95	—	Unverified
7	GGCM	Accuracy	80.8	—	Unverified
8	GCN(predicted-targets)	Accuracy	80.42	—	Unverified
9	SSGC	Accuracy	80.4	—	Unverified
10	GCNII	Accuracy	80.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OGC	Accuracy	86.9	—	Unverified
2	GCN-TV	Accuracy	86.3	—	Unverified
3	GCNII	Accuracy	85.5	—	Unverified
4	CPF-ind-APPNP	Accuracy	85.3	—	Unverified
5	AIR-GCN	Accuracy	84.7	—	Unverified
6	H-GCN	Accuracy	84.5	—	Unverified
7	G-APPNP	Accuracy	84.31	—	Unverified
8	SuperGAT MX	Accuracy	84.3	—	Unverified
9	DSGCN	Accuracy	84.2	—	Unverified
10	LDS-GNN	Accuracy	84.1	—	Unverified