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 1226–1250 of 1860 papers

Title	Date	Tasks	Status
Structure-Aware Label Smoothing for Graph Neural Networks	Dec 1, 2021	ClassificationNode Classification	—Unverified
Structure fusion based on graph convolutional networks for semi-supervised classification	Jul 2, 2019	ClassificationGeneral Classification	—Unverified
Subgraph Attention for Node Classification and Hierarchical Graph Pooling	Sep 25, 2019	ClassificationGraph Classification	—Unverified
Superiority of GNN over NN in generalizing bandlimited functions	Jun 13, 2022	Node Classification	—Unverified
Supervised Attention Using Homophily in Graph Neural Networks	Jul 11, 2023	Graph AttentionNode Classification	—Unverified
Supervised Contrastive Learning with Structure Inference for Graph Classification	Mar 15, 2022	ClassificationContrastive Learning	—Unverified
Supervised Q-walk for Learning Vector Representation of Nodes in Networks	Oct 3, 2017	ClassificationGeneral Classification	—Unverified
Surrogate Representation Learning with Isometric Mapping for Gray-box Graph Adversarial Attacks	Oct 20, 2021	Node ClassificationRepresentation Learning	—Unverified
Symplectic Structure-Aware Hamiltonian (Graph) Embeddings	Sep 9, 2023	Node ClassificationRiemannian optimization	—Unverified
SynHING: Synthetic Heterogeneous Information Network Generation for Graph Learning and Explanation	Jan 7, 2024	Graph LearningInterpretable Machine Learning	—Unverified
Synthetic Graph Generation to Benchmark Graph Learning	Apr 4, 2022	Graph GenerationGraph Learning	—Unverified
Synthetic Over-sampling for Imbalanced Node Classification with Graph Neural Networks	Jun 10, 2022	Node Classification	—Unverified
Deeper-GXX: Deepening Arbitrary GNNs	Oct 26, 2021	Contrastive LearningLink Prediction	—Unverified
Teaching Yourself: Graph Self-Distillation on Neighborhood for Node Classification	Oct 5, 2022	ClassificationNode Classification	—Unverified
Teleport Graph Convolutional Networks	Jan 1, 2021	Node Classification	—Unverified
Topology-aware Tensor Decomposition for Meta-graph Learning	Jan 4, 2021	Graph LearningKnowledge Graphs	—Unverified
Text Representation Enrichment Utilizing Graph based Approaches: Stock Market Technical Analysis Case Study	Nov 29, 2022	ClassificationDocument Classification	—Unverified
TPM: Transition Probability Matrix -- Graph Structural Feature based Embedding	Aug 7, 2022	Link PredictionNode Classification	—Unverified
The Linearization of Belief Propagation on Pairwise Markov Networks	Feb 17, 2015	Node Classification	—Unverified
The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs	May 12, 2021	BIG-bench Machine LearningNode Classification	—Unverified
There is more to graphs than meets the eye: Learning universal features with self-supervision	May 31, 2023	Node ClassificationRepresentation Learning	—Unverified
TiGer: Self-Supervised Purification for Time-evolving Graphs	Mar 10, 2025	Node Classification	—Unverified
Time-Aware Neighbor Sampling for Temporal Graph Networks	Dec 18, 2021	Node Classification	—Unverified
TNE: A Latent Model for Representation Learning on Networks	Oct 16, 2018	Community DetectionLink Prediction	—Unverified
Tokenized Graph Transformer with Neighborhood Augmentation for Node Classification in Large Graphs	May 22, 2023	Data AugmentationGraph Representation Learning	—Unverified

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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	Cleora	Accuracy	86.8	—	Unverified
7	NodeNet	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